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+Menu: [Computer Science](cmpsc.md) | [Electronics](electronics.md) | [Machine Learning](machine_learning.md) | [Mathematics](math.md) | [Quant Trading](quant_trading.md) | [Physics](physics.md) |
+
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-Menu: [[file:cmpsc.org][Computer Science]] | [[file:electronics.org][Electronics]] | [[file:machine_learning.org][Machine Learning]] | [[file:math.org][Mathematics]] | [[file:quant_trading.org][Quant Trading]] | [[file:physics.org][Physics]] |
-
-* CRISPR
-
-+ http://gizmodo.com/everything-you-need-to-know-about-crispr-the-new-tool-1702114381
-+ http://www.radiolab.org/story/antibodies-part-1-crispr/
diff --git a/cmpsc.md b/cmpsc.md
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+# Computer Science
+
+## Short List
+
+- https://github.com/open-source-society/computer-science - Path to a free self-taught education in Computer Science
+
+## Inbox
+
+- [Pathfinding Demystified (Part I): Generic Search Algorithm](https://gabrielgambetta.com/generic-search.html)
+   - https://news.ycombinator.com/item?id=22231597
+- [MIT 6.006 Fall 2011 Algorithms](https://news.ycombinator.com/item?id=20977731)
+- [Introduction to Genetic Algorithms](https://blog.floydhub.com/introduction-to-genetic-algorithms/)
+   - https://news.ycombinator.com/item?id=20118292
+- [Bloom Filters by Example](https://llimllib.github.io/bloomfilter-tutorial/)
+   - https://news.ycombinator.com/item?id=19897444
+- [Stanford CS166 Data Structures](http://web.stanford.edu/class/cs166/)
+    - https://news.ycombinator.com/item?id=19780387
+- [Dynamic programming for fun and profit](https://reindeereffect.github.io/2018/03/08/options-valuation/)
+- [A graphical introduction to dynamic programming](https://avikdas.com/2019/04/15/a-graphical-introduction-to-dynamic-programming.html)
+- https://news.ycombinator.com/item?id=15409757 B-trees
+- [A Short History of the BTree](https://www.perforce.com/blog/110928/short-history-btree)
+- [The MIT Challenge](https://www.scotthyoung.com/blog/myprojects/mit-challenge-2/)
+- [Language Detection using N-Grams](http://cloudmark.github.io/Language-Detection/)
+- [Some Starting Points for Deep Learning and RNNs](http://www.aistartups.org/2016/03/some-starting-points-for-deep-learning.html)
+ - https://news.ycombinator.com/item?id=11337741
+- https://news.ycombinator.com/item?id=10398057 - Warping Text to a Bézier curves
+- http://www.bionicspirit.com/blog/2012/02/09/howto-build-naive-bayes-classifier.html
+- http://news.ycombinator.com/item?id=10246348 - How to Determine If Four Points Make a Square 
+- https://news.ycombinator.com/item?id=10171469 - CS Unplugged
+- http://news.ycombinator.com/item?id=10129914 - Pixar in a Box
+- http://news.ycombinator.com/item?id=9940126 - Spreadsheets
+- [Rubik's Cube Solution](http://news.ycombinator.com/item?id=9850914)
+- [Thoughts on Time Series Databases](http://news.ycombinator.com/item?id=9805742)
+- [Making reliable distributed systems in the presence of sofware errors](http://www.erlang.org/download/armstrong_thesis_2003.pdf)
+- http://optics.byu.edu/textbook.aspx
+- http://henrikwarne.com/2015/04/16/lessons-learned-in-software-development
+- http://www.gamasutra.com/blogs/ChrisSimpson/20140717/221339/Behavior_trees_for_AI_How_they_work.php 
+- http://news.ycombinator.com/item?id=6972765 - Great books about mathematics (kjro.se)
+- http://jeremykun.com/2014/02/10/elliptic-curves-as-elementary-equations
+- http://engineering.foursquare.com/2014/01/03/the-mathematics-of-gamification
+- http://news.ycombinator.com/item?id=6820547 - Why are software development estimates regularly off by a factor of 2-3?
+- http://luisbg.blogalia.com/historias/74062 - Basic Data Structures and Algorithms in the Linux Kernel
+- http://thewe.net/math/conway.pdf - The Power of Mathematics
+- http://news.ycombinator.com/item?id=7285522 - Salted Password Hashing – Doing it Right
+- http://www.mazeworks.com/mazegen/mazetut/index.htm
+   - http://news.ycombinator.com/item?id=7458848 - How To Build A Maze (mazeworks.com)
+- http://news.ycombinator.com/item?id=7746822 - Maze Tree (ocks.org)
+- http://news.ycombinator.com/item?id=8790680
+- http://java.dzone.com/articles/idiots-guide-big-o
+- http://github.com/prakhar1989/awesome-courses/blob/master/README.md
+   - http://news.ycombinator.com/item?id=8806910
+- http://news.ycombinator.com/item?id=8806475 - String Matching 
+- [Neat Algorithms: Paxos](http://news.ycombinator.com/item?id=8806835)
+- [Deep Learning Reading List](http://news.ycombinator.com/item?id=8813484)
+- [Code for Game Developers - Big O Notation - Video](http://www.youtube.com/watch?v=CTSNBaOkjOQ)
+- http://techeffigytutorials.blogspot.com/2015/01/markov-chains-explained.html
+- [Out of the Tarpit](http://raw.githubusercontent.com/papers-we-love/papers-we-love/master/design/out-of-the-tar-pit.pdf)
+- http://news.ycombinator.com/item?id=8835085 - The Game AI Programmer's Bookshelf
+- http://news.ycombinator.com/item?id=8825728 - Ask HN: What are some nice electronics courses that blend theory and practice?
+- http://news.ycombinator.com/item?id=8825750 - The “What Are Monads?” Fallacy (two-wrongs.com)
+- http://news.ycombinator.com/item?id=8943356 - A practical introduction to functional programming 
+- http://news.ycombinator.com/item?id=8943142 - Papers We Love
+- http://news.ycombinator.com/item?id=8918259 - Eigenvectors and eigenvalues explained visually
+- http://news.ycombinator.com/item?id=8912219 - Extracting text from an image using Ocropus
+- http://news.ycombinator.com/item?id=8898299 - Rules for Developing Safety Critical Code [pdf] 
+- http://news.ycombinator.com/item?id=7082939 - How Radians Work in 30 Seconds (googleusercontent.com)
+- http://williamedwardscoder.tumblr.com/post/87682811573/compressing-scrabble-dictionaries
+- http://www.quantstart.com/articles/Value-at-Risk-VaR-for-Algorithmic-Trading-Risk-Management-Part-I
+- http://news.ycombinator.com/item?id=8059237 - Introduction to A* (redblobgames.com)
+- http://news.ycombinator.com/item?id=8082434 - Math Intuition Cheatsheet (betterexplained.com)
+- http://spin.atomicobject.com/2014/08/11/fisher-yates-shuffle-randomization-algorithm
+- http://news.ycombinator.com/item?id=8159424 - Introduction to Signal Processing
+- http://news.ycombinator.com/item?id=8103240 - Show HN: Markov chains explained visually (setosa.io)
+- http://www.thomsett.com.au/library/item/estimation-games
+- http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
+- http://raymii.org/s/articles/Solve_word_puzzles_with_bash.html
+
+## Books
+
+- [Mathematics and Computation](https://www.math.ias.edu/files/Website03-25-19.pdf)
+    - https://news.ycombinator.com/item?id=19609613
+- [Mathematics for Computer Science (pdf)](https://courses.csail.mit.edu/6.042/spring17/mcs.pdf)
+    - https://news.ycombinator.com/item?id=13800320
+- [Algorithms - Jeff Erikson](http://jeffe.cs.illinois.edu/teaching/algorithms/)
+   - https://news.ycombinator.com/item?id=20733923
+   - https://news.ycombinator.com/item?id=18805624
+
+
+## SICP
+
+- [SICP in Python 3 from Berkeley](http://composingprograms.com/)
+   - https://news.ycombinator.com/item?id=11465234
+   - https://news.ycombinator.com/item?id=3491142
+   - https://news.ycombinator.com/item?id=3141996
+   - https://mitpress.mit.edu/sicp/
+- [Structure and Interpretation of Computer Programs](http://sarabander.github.io/sicp/html/index.xhtml)
+- [CS 61AS - Spring 2016](http://www.cs61as.org)
+
+## Data Science
+
+- [Harvard CS109 Data Science](http://cs109.org)
+   - [First Video](http://cm.dce.harvard.edu/2016/01/14328/L01/mobile_Mp4TalkingHeadSlideVideo-1.shtml?part=1)
+
+## NLP
+
+- [oxford-cs-deepnlp-2017](https://github.com/oxford-cs-deepnlp-2017)
+  - https://news.ycombinator.com/item?id=13588070
+- [How To Get Into Natural Language Processing](https://blog.ycombinator.com/how-to-get-into-natural-language-processing/)
+   - https://news.ycombinator.com/item?id=13445255
+- [Dan Jurafsky & Chris Manning: Natural Language Processing](https://m.youtube.com/playlist?list=PL6397E4B26D00A269)
+
+##  Software Development
+
+- [Design Pattern – An Introduction](http://www.knowstack.com/design-pattern-an-introduction)
+- [Making a toy programming language in Lua, part 2](http://www.playwithlua.com/?p=68)
+
+
+## Text Editors
+
+- [The Craft of Text Editing](https://www.finseth.com/craft/)
+   - https://news.ycombinator.com/item?id=13518170
+ 
+
+## Algorithms
+
+- [MIT 6.851: Advanced Data Structures (Fall'17)](https://courses.csail.mit.edu/6.851/fall17/)
+   - https://news.ycombinator.com/item?id=20044876
+- https://github.com/trekhleb/javascript-algorithms
+- http://visualgo.net
+- http://www.cs.usfca.edu/~galles/visualization/Algorithms.html
+- [The Algorithmist](https://www.algorithmist.com/index.php/Main_Page)
+   - http://news.ycombinator.com/item?id=10155498
+- http://schani.wordpress.com/2010/04/30/linear-vs-binary-search
+- http://news.ycombinator.com/item?id=9660185 - OpenCV
+- http://wwwold.cs.umd.edu/class/fall2002/cmsc818s/Readings/b-tree.pdf
+- [Ask HN: Any recomendations...](https://news.ycombinator.com/item?id=12669054)
+- http://bigocheatsheet.com
+- [The Linear Algebra Behind Google](https://www.rose-hulman.edu/~bryan/googleFinalVersionFixed.pdf)
+   - https://news.ycombinator.com/item?id=9951329
+-  Bloom filters - fast way to test for set membership with less memory
+- [Substring search algorithm](http://volnitsky.com/project/str_search/index.html)
+   - https://news.ycombinator.com/item?id=10294982
+- https://medium.com/@nickgerleman/the-bkd-tree-da19cf9493fb
+- https://www.programmingalgorithms.com/algorithm/day-of-week
+   - https://news.ycombinator.com/item?id=11358999
+- [The Rete Matching Algorithm]([http://www.drdobbs.com/architecture-and-design/the-rete-matching-algorithm/184405218)
+    - https://news.ycombinator.com/item?id=11364718
+- https://rob-bell.net/2009/06/a-beginners-guide-to-big-o-notation/
+    - https://news.ycombinator.com/item?id=11636002
+- [Sorting Algorithm Animations](http://www.sorting-algorithms.com)
+    - https://news.ycombinator.com/item?id=11783526
+- https://lettier.github.io/posts/2016-06-10-k-nearest-neighbors-from-scratch.html
+    - https://news.ycombinator.com/item?id=11906759
+- [UC Davis Course](http://www.youtube.com/playlist?list=PL_w_qWAQZtAZ2n35UD2FHgvbXj4pqPQq5)
+
+## Data Structures
+
+- http://news.ycombinator.com/item?id=7079427 - What are the lesser known but useful data structures? (stackoverflow.com)
+
+
+## Search
+
+- [Document Clustering with Python](http://brandonrose.org/clustering)
+   - https://news.ycombinator.com/item?id=10402177
+
+
+## Sorting
+
+- https://m.imgur.com/gallery/GD5gi
+
+
+## Bayes Theorem
+
+- [Bayes’ Theorem: What is it and what is it good for?](http://crucialconsiderations.org/rationality/bayes-theorem/)
+   - http://news.ycombinator.com/item?id=9780677
+- [A Tutorial on Learning With Bayesian Networks](https://www.microsoft.com/en-us/research/publication/a-tutorial-on-learning-with-bayesian-networks/)
+   - http://news.ycombinator.com/item?id=9980716
+- [Using Bayes Factors to Get the Most out of Linear Regression: A Practical Guide Using R](https://thewinnower.com/papers/278-using-bayes-factors-to-get-the-most-out-of-linear-regression-a-practical-guide-using-r)
+- [Think Bayes](http://www.greenteapress.com/thinkbayes/) - Creative Commons O'Reilly Book
+
+
+## Gaming
+
+- [Supreme Commander – Graphics Study](https://news.ycombinator.com/item?id=9770020)
+- http://news.ycombinator.com/item?id=9537009 -  Implementation of Hex Grids
+- http://news.ycombinator.com/item?id=8584695 - Essential Math for Games Programmers (essentialmath.com
+- http://news.ycombinator.com/item?id=8200160 - Amit's Game Programming Information (stanford.edu)
+- http://higherorderfun.com/blog/2010/02/23/math-for-game-programmers-04-operations-on-vectors
+- http://news.ycombinator.com/item?id=9054290 - Procedural City Generation (tmwhere.com)
+- http://news.ycombinator.com/item?id=8708541 - Pathfinding for Tower Defense (redblobgames.com)
+- http://news.ycombinator.com/item?id=9086791 - Optimizing A* for grid map
+- http://www.gamedev.net/page/resources/_/technical/game-programming/doom3-is-the-proof-that-keep-it-simple-works-r4009
+ - http://news.ycombinator.com/item?id=9302637
+- https://news.ycombinator.com/item?id=10171792
+
+## Maze Generation and Grids
+
+- http://www.gridsagegames.com/blog/2016/03/generating-populating-caves/
+- http://journal.stuffwithstuff.com/2014/12/21/rooms-and-mazes/
+- http://simblob.blogspot.com/2015/02/optimizing-for-grid-maps.html
+   - http://news.ycombinator.com/item?id=9086791
+
+
+## Doom
+- https://news.ycombinator.com/item?id=10787747
+
+
+## Libraries
+
+- [Open Source OCR](https://news.ycombinator.com/item?id=9775753)
diff --git a/cmpsc.org b/cmpsc.org
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+++ /dev/null
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-#+STARTUP: showall
-#+TITLE: Computer Science
-#+AUTHOR: http://h4labs.com
-#+EMAIL: melling@h4labs.com
-
-* Short List
-+ https://github.com/open-source-society/computer-science - Path to a free self-taught education in Computer Science
-
-* Inbox
-+ https://news.ycombinator.com/item?id=15409757 B-trees
-+ [[https://courses.csail.mit.edu/6.042/spring17/mcs.pdf][Mathematics for Computer Science (pdf)]]
-   - https://news.ycombinator.com/item?id=13800320
-+ [[https://www.perforce.com/blog/110928/short-history-btree][A Short History of the BTree]]
-+ [[https://www.scotthyoung.com/blog/myprojects/mit-challenge-2/][The MIT Challenge]]
-+ [[http://cloudmark.github.io/Language-Detection/][Language Detection using N-Grams]]
-+ [[http://www.aistartups.org/2016/03/some-starting-points-for-deep-learning.html][Some Starting Points for Deep Learning and RNNs]]
- - https://news.ycombinator.com/item?id=11337741
-+ https://news.ycombinator.com/item?id=10398057 - Warping Text to a Bézier curves
-+ http://www.bionicspirit.com/blog/2012/02/09/howto-build-naive-bayes-classifier.html
-+ http://news.ycombinator.com/item?id=10246348 - How to Determine If Four Points Make a Square 
-+ https://news.ycombinator.com/item?id=10171469 - CS Unplugged
-+ http://news.ycombinator.com/item?id=10129914 - Pixar in a Box
-+ http://news.ycombinator.com/item?id=9940126 - Spreadsheets
-+ [[http://news.ycombinator.com/item?id=9850914][Rubik's Cube Solution]]
-+ [[http://news.ycombinator.com/item?id=9805742][Thoughts on Time Series Databases]]
-+ [[http://www.erlang.org/download/armstrong_thesis_2003.pdf][Making reliable distributed systems in the presence of sofware errors]]
-+ http://optics.byu.edu/textbook.aspx
-+ http://henrikwarne.com/2015/04/16/lessons-learned-in-software-development
-+ http://www.gamasutra.com/blogs/ChrisSimpson/20140717/221339/Behavior_trees_for_AI_How_they_work.php 
-+ http://news.ycombinator.com/item?id=6972765 - Great books about mathematics (kjro.se)
-+ http://jeremykun.com/2014/02/10/elliptic-curves-as-elementary-equations
-+ http://engineering.foursquare.com/2014/01/03/the-mathematics-of-gamification
-+ http://news.ycombinator.com/item?id=6820547 - Why are software development estimates regularly off by a factor of 2-3?
-+ http://luisbg.blogalia.com/historias/74062 - Basic Data Structures and Algorithms in the Linux Kernel
-+ http://thewe.net/math/conway.pdf - The Power of Mathematics
-+ http://news.ycombinator.com/item?id=7285522 - Salted Password Hashing – Doing it Right
-+ http://www.mazeworks.com/mazegen/mazetut/index.htm
- - http://news.ycombinator.com/item?id=7458848 - How To Build A Maze (mazeworks.com)
-+ http://news.ycombinator.com/item?id=7746822 - Maze Tree (ocks.org)
-+ http://news.ycombinator.com/item?id=8790680
-+ http://java.dzone.com/articles/idiots-guide-big-o
-+ http://github.com/prakhar1989/awesome-courses/blob/master/README.md
- - http://news.ycombinator.com/item?id=8806910
-+ http://news.ycombinator.com/item?id=8806475 - String Matching 
-+ [[http://news.ycombinator.com/item?id=8806835][Neat Algorithms: Paxos]]
-+ [[http://news.ycombinator.com/item?id=8813484][Deep Learning Reading List]]
-+ http://www.youtube.com/watch?v=CTSNBaOkjOQ
-+ http://techeffigytutorials.blogspot.com/2015/01/markov-chains-explained.html
-+ [[http://raw.githubusercontent.com/papers-we-love/papers-we-love/master/design/out-of-the-tar-pit.pdf][Out of the Tarpit]]
-+ http://news.ycombinator.com/item?id=8835085 - The Game AI Programmer's Bookshelf
-+ http://news.ycombinator.com/item?id=8825728 - Ask HN: What are some nice electronics courses that blend theory and practice?
-+ http://news.ycombinator.com/item?id=8825750 - The “What Are Monads?” Fallacy (two-wrongs.com)
-+ http://news.ycombinator.com/item?id=8943356 - A practical introduction to functional programming 
-+ http://news.ycombinator.com/item?id=8943142 - Papers We Love
-+ http://news.ycombinator.com/item?id=8918259 - Eigenvectors and eigenvalues explained visually
-+ http://news.ycombinator.com/item?id=8912219 - Extracting text from an image using Ocropus
-+ http://news.ycombinator.com/item?id=8898299 - Rules for Developing Safety Critical Code [pdf] 
-+ http://news.ycombinator.com/item?id=7082939 - How Radians Work in 30 Seconds (googleusercontent.com)
-+ http://williamedwardscoder.tumblr.com/post/87682811573/compressing-scrabble-dictionaries
-+ http://www.quantstart.com/articles/Value-at-Risk-VaR-for-Algorithmic-Trading-Risk-Management-Part-I
-+ http://news.ycombinator.com/item?id=8059237 - Introduction to A* (redblobgames.com)
-+ http://news.ycombinator.com/item?id=8082434 - Math Intuition Cheatsheet (betterexplained.com)
-+ http://spin.atomicobject.com/2014/08/11/fisher-yates-shuffle-randomization-algorithm
-+ http://news.ycombinator.com/item?id=8159424 - Introduction to Signal Processing
-+ http://news.ycombinator.com/item?id=8103240 - Show HN: Markov chains explained visually (setosa.io)
-+ http://www.thomsett.com.au/library/item/estimation-games
-+ http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
-+ http://raymii.org/s/articles/Solve_word_puzzles_with_bash.html
-
-* SICP
-+ [[http://composingprograms.com/][SICP in Python 3 from Berkeley]]
- - https://news.ycombinator.com/item?id=11465234
- - https://news.ycombinator.com/item?id=3491142
- - https://news.ycombinator.com/item?id=3141996
-+ https://mitpress.mit.edu/sicp/
-+ [[http://sarabander.github.io/sicp/html/index.xhtml][Structure and Interpretation of Computer Programs]]
-+ [[http://www.cs61as.org][CS 61AS - Spring 2016]]
-
-* Data Science
-+ [[http://cs109.org][Harvard CS109 Data Science]]
- - [[http://cm.dce.harvard.edu/2016/01/14328/L01/mobile_Mp4TalkingHeadSlideVideo-1.shtml?part=1][First Video]]
-
-* NLP
-+ [[https://github.com/oxford-cs-deepnlp-2017][oxford-cs-deepnlp-2017]]
- - https://news.ycombinator.com/item?id=13588070
-+ [[https://blog.ycombinator.com/how-to-get-into-natural-language-processing/][How To Get Into Natural Language Processing]]
- - https://news.ycombinator.com/item?id=13445255
-+ [[https://m.youtube.com/playlist?list=PL6397E4B26D00A269][Dan Jurafsky & Chris Manning: Natural Language Processing]]
-
-* Software Development
-+ http://www.knowstack.com/design-pattern-an-introduction
-+ http://www.playwithlua.com/?p=68
-+ http://www.vnev.me/implementing-a-programming-language-in-c-part-2 
-  - https://news.ycombinator.com/item?id=9688258
-
-* Text Editors
-+ [[https://www.finseth.com/craft/][The Craft of Text Editing]]
- - https://news.ycombinator.com/item?id=13518170
- 
-* Algorithms
-+ http://visualgo.net
-+ http://www.cs.usfca.edu/~galles/visualization/Algorithms.html
-+ http://news.ycombinator.com/item?id=10155498
-+ http://schani.wordpress.com/2010/04/30/linear-vs-binary-search
-+ http://news.ycombinator.com/item?id=9660185 - OpenCV
-+ http://wwwold.cs.umd.edu/class/fall2002/cmsc818s/Readings/b-tree.pdf
-+ https://news.ycombinator.com/item?id=12669054
-+ http://bigocheatsheet.com
-+ https://news.ycombinator.com/item?id=9951329
-+ Bloom filters - fast way to test for set membership with less memory
-+ https://news.ycombinator.com/item?id=10294982
-+ https://medium.com/@nickgerleman/the-bkd-tree-da19cf9493fb
-+ https://www.programmingalgorithms.com/algorithm/day-of-week
- - https://news.ycombinator.com/item?id=11358999
-+ [[http://www.drdobbs.com/architecture-and-design/the-rete-matching-algorithm/184405218][The Rete Matching Algorithm]]
- https://news.ycombinator.com/item?id=11364718
-+ https://rob-bell.net/2009/06/a-beginners-guide-to-big-o-notation/
- - https://news.ycombinator.com/item?id=11636002
-+ [[http://www.sorting-algorithms.com][Sorting Algorithm Animations]]
- - https://news.ycombinator.com/item?id=11783526
-+ https://lettier.github.io/posts/2016-06-10-k-nearest-neighbors-from-scratch.html
- - https://news.ycombinator.com/item?id=11906759
-+ [[http://www.youtube.com/playlist?list=PL_w_qWAQZtAZ2n35UD2FHgvbXj4pqPQq5][UC Davis Course]]
-
-* Data Structures
-+ http://news.ycombinator.com/item?id=7079427 - What are the lesser known but useful data structures? (stackoverflow.com)
-
-* Search
-
-+ https://news.ycombinator.com/item?id=10402177 
-+ https://news.ycombinator.com/item?id=10403820
-
-* Sorting
-+ https://m.imgur.com/gallery/GD5gi
-
-* Mathematics
-+ http://news.ycombinator.com/item?id=9927909
-+ [[http://news.ycombinator.com/item?id=9715149][Guide to Writing Mathematics]]
-+ http://jeremykun.com/2015/06/08/methods-of-proof-diagonalization
-+ http://news.ycombinator.com/item?id=8348769 - How Not to Lie with Statistics: Avoiding Common Mistakes (1986) [pdf]
-+ http://proofs.wiki/Main_Page
-+ http://blog.circuitsofimagination.com/2015/02/15/Markov-Chains.html
-+ http://news.ycombinator.com/item?id=9040051 - An Introduction to the Central Limit Theorem
-+ http://www.countbayesie.com/blog/2015/2/21/variance-co-variance-and-correlation
-+ http://web.mit.edu/18.06/www/videos.shtml
-+ http://classmill.com/jennathompson/introduction-to-algebra
-+ http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/video-lectures
-
-** Bayes Theorem
-+ http://news.ycombinator.com/item?id=9780677
-+ http://news.ycombinator.com/item?id=9980716
-+ https://thewinnower.com/papers/278-using-bayes-factors-to-get-the-most-out-of-linear-regression-a-practical-guide-using-r
-+ http://www.greenteapress.com/thinkbayes/ - Creative Commons O'Reilly Book
-
-* Gaming
-+ [[https://news.ycombinator.com/item?id=9770020][Supreme Commander – Graphics Study]]
-+ http://news.ycombinator.com/item?id=9537009 -  Implementation of Hex Grids
-+ http://news.ycombinator.com/item?id=8584695 - Essential Math for Games Programmers (essentialmath.com
-+ http://news.ycombinator.com/item?id=8200160 - Amit's Game Programming Information (stanford.edu)
-+ http://higherorderfun.com/blog/2010/02/23/math-for-game-programmers-04-operations-on-vectors
-+ http://news.ycombinator.com/item?id=9054290 - Procedural City Generation (tmwhere.com)
-+ http://news.ycombinator.com/item?id=8708541 - Pathfinding for Tower Defense (redblobgames.com)
-+ http://news.ycombinator.com/item?id=9086791 - Optimizing A* for grid map
-+ http://www.gamedev.net/page/resources/_/technical/game-programming/doom3-is-the-proof-that-keep-it-simple-works-r4009
- - http://news.ycombinator.com/item?id=9302637
-+ https://news.ycombinator.com/item?id=10171792
-
-* Maze Generation and Grids
-+ http://www.gridsagegames.com/blog/2016/03/generating-populating-caves/
-+ http://journal.stuffwithstuff.com/2014/12/21/rooms-and-mazes/
-+ http://simblob.blogspot.com/2015/02/optimizing-for-grid-maps.html
- - http://news.ycombinator.com/item?id=9086791
-
-
-** Doom
-+ https://news.ycombinator.com/item?id=10787747
-
-
-* Libraries 
-+ [[https://news.ycombinator.com/item?id=9775753][Open Source OCR]]
diff --git a/data_science.md b/data_science.md
new file mode 100644
index 0000000..63b42a5
--- /dev/null
+++ b/data_science.md
@@ -0,0 +1,15 @@
+# Data Science
+
+## Interview Questions
+
+
+- [40 Statistics Interview Problems and Answers for Data Scientists ](https://towardsdatascience.com/40-statistics-interview-problems-and-answers-for-data-scientists-6971a02b7eee)
+- [Amazon’s Data Scientist Interview Practice Problems ](https://towardsdatascience.com/amazon-data-scientist-interview-practice-problems-15b9b86e86c6)
+- [Microsoft Data Science Interview Questions and Answers](https://towardsdatascience.com/microsoft-data-science-interview-questions-and-answers-69ccac16bd9b)
+- [160+ Data Science Interview Questions](https://hackernoon.com/160-data-science-interview-questions-415s3y2a)
+- [The Most Comprehensive Stats Cheat Sheet](https://medium.com/@terenceshin/week-2-52-stats-cheat-sheet-ae38a2e5cdc6)
+
+## Books
+
+- https://www.amazon.com/Data-Science-Scratch-Principles-Python/dp/1492041130/
+- https://www.amazon.com/Introduction-Statistical-Learning-Applications-Statistics/dp/1461471370/
diff --git a/economics.md b/economics.md
new file mode 100644
index 0000000..8e8356d
--- /dev/null
+++ b/economics.md
@@ -0,0 +1,19 @@
+# Economics
+
+## Inbox
+
+- https://www.brookings.edu/blog/up-front/2019/06/06/how-will-we-know-when-a-recession-is-coming/
+   - Sahm Recession Indicator
+- https://en.m.wikipedia.org/wiki/Total_factor_productivity
+
+## Topics
+
+- [Trimmed Mean PCE Inflation Rate](https://www.dallasfed.org/research/pce.aspx)
+
+
+## Books
+
+- https://www.goodreads.com/book/show/20613671-economics
+- http://www.hup.harvard.edu/catalog.php?isbn=9780674016095&content=reviews
+- https://filmlifestyle.com/best-economics-books/
+  - https://news.ycombinator.com/item?id=20154382
diff --git a/electronics.md b/electronics.md
new file mode 100644
index 0000000..fa2be84
--- /dev/null
+++ b/electronics.md
@@ -0,0 +1,6 @@
+
+# Electronics
+
+
+## Inbox
+- https://www.stavros.io/posts/building-cheap-home-sensorcontroller
diff --git a/electronics.org b/electronics.org
deleted file mode 100644
index a8d42a9..0000000
--- a/electronics.org
+++ /dev/null
@@ -1,7 +0,0 @@
-#+STARTUP: showall
-#+TITLE: Electronics
-#+AUTHOR: http://h4labs.com
-#+EMAIL: melling@h4labs.com
-
-* Inbox
-+ https://www.stavros.io/posts/building-cheap-home-sensorcontroller
diff --git a/machine_learning.md b/machine_learning.md
new file mode 100644
index 0000000..1e83a02
--- /dev/null
+++ b/machine_learning.md
@@ -0,0 +1,135 @@
+# Machine Learning
+
+
+## Inbox
+
+- [Computer Vision Basics in Microsoft Excel](https://github.com/amzn/computer-vision-basics-in-microsoft-excel)
+   - https://news.ycombinator.com/item?id=22357374
+- http://www.gameaipro.com/
+- [Understanding Machine Learning: From Theory to Algorithms - PDF](https://www.cse.huji.ac.il/~shais/UnderstandingMachineLearning/copy.html)
+- http://www.oranlooney.com/post/ml-from-scratch-part-1-linear-regression/
+   - https://news.ycombinator.com/item?id=21298233
+- https://mml-book.github.io/
+   - https://news.ycombinator.com/item?id=21293132
+- https://ngoldbaum.github.io/posts/python-vs-rust-nn/
+   - https://news.ycombinator.com/item?id=20728288
+- [The Matrix Calculus You Need for Deep Learning](https://arxiv.org/pdf/1802.01528.pdf)
+   - https://www.lesswrong.com/posts/9L9XuXhLYBm47yYkf/a-primer-on-matrix-calculus-part-1-basic-review
+   - https://www.lesswrong.com/posts/KKwv9kcQz29vqPLAD/a-primer-on-matrix-calculus-part-2-jacobians-and-other-fun
+   - https://www.lesswrong.com/posts/u4DWp72GyLsQn24oR/a-primer-on-matrix-calculus-part-3-the-chain-rule
+- https://news.ycombinator.com/item?id=20674745
+- http://www.cis.upenn.edu/~jean/math-basics.pdf
+   - https://news.ycombinator.com/item?id=20570025
+- [Population based training of neural networks](https://deepmind.com/blog/population-based-training-neural-networks/)
+- [L2 Regularization and Batch Norm](https://blog.janestreet.com/l2-regularization-and-batch-norm/)
+   - https://news.ycombinator.com/item?id=20504695
+- [Meta-learning neural Bloom filters](https://blog.acolyer.org/2019/07/19/meta-learning-neural-bloom-filters/)
+- http://www.datastuff.tech/machine-learning/why-do-neural-networks-need-an-activation-function/
+- [fast.ai: Deep Learning from the Foundations](https://www.fast.ai/2019/06/28/course-p2v3/)
+   - https://news.ycombinator.com/item?id=20312714
+- [Logistic Regression from Bayes' Theorem](https://www.countbayesie.com/blog/2019/6/12/logistic-regression-from-bayes-theorem)
+- [GANs World Resources](https://github.com/machinelearningmindset/Generative-Adversarial-Networks-Roadmap)
+- [MIT 6.S191 Introduction to Deep Learning](http://introtodeeplearning.com/)
+   - [Videos Winter 2019 - 2018 Videos 10-20 ](http://www.youtube.com/watch?v=5v1JnYv_yWs&list=PLtBw6njQRU-rwp5__7C0oIVt26ZgjG9NI)
+   - [Videos Winter 2017](https://www.youtube.com/playlist?list=PLkkuNyzb8LmxFutYuPA7B4oiMn6cjD6Rs)
+   - https://github.com/edwinksl/6.S191
+- [MIT 18.065 - Spring 2018: Matrix Methods in Data Analysis, Signal Processing, and Machine Learning](https://ocw.mit.edu/courses/mathematics/18-065-matrix-methods-in-data-analysis-signal-processing-and-machine-learning-spring-2018/)
+   - https://news.ycombinator.com/item?id=19933274
+   - [YouTube Playlist](https://www.youtube.com/playlist?list=PLUl4u3cNGP63oMNUHXqIUcrkS2PivhN3k)
+- [Machine Learning Course with Python](https://github.com/machinelearningmindset/machine-learning-course)
+   - https://news.ycombinator.com/item?id=19886754
+- [Learn_Machine_Learning_in_3_Months](https://github.com/llSourcell/Learn_Machine_Learning_in_3_Months)
+- [A Recipe for Training Neural Networks](https://karpathy.github.io/2019/04/25/recipe/)
+- [A visual proof that neural nets can compute any function](http://neuralnetworksanddeeplearning.com/chap4.html)
+    - https://news.ycombinator.com/item?id=19708620
+- [Kalman and Bayesian Filters in Python](https://github.com/rlabbe/Kalman-and-Bayesian-Filters-in-Python)
+    - https://news.ycombinator.com/item?id=19672039
+- [What is a Manifold](https://bastian.rieck.me/blog/posts/2019/manifold)
+    - https://news.ycombinator.com/item?id=19658558
+- https://news.ycombinator.com/item?id=19499515
+- [Illustrated word2vec](https://jalammar.github.io/illustrated-word2vec/)
+    - https://news.ycombinator.com/item?id=19498356
+- [The Illustrated Transformer](http://jalammar.github.io/illustrated-transformer/)
+- http://bugra.github.io/work/notes/2014-08-23/on-machine-learning/
+- [Machine Learning - HN](https://news.ycombinator.com/item?id=10782909)
+- [Deep Learning - Ian Goodfellow, Yoshua Bengio and Aaron Courville](http://www.deeplearningbook.org)
+  - https://news.ycombinator.com/item?id=11446164
+- http://datanice.github.io/machine-learning-101-what-is-regularization-interactive.html
+  - https://news.ycombinator.com/item?id=11906844
+  
+## Build from Scratch
+
+- https://smalldata.tech/blog/2016/05/03/building-a-simple-neural-net-in-java
+- [Neural networks from scratch in Scala](https://github.com/botkop/numsca/blob/master/notebooks/dl-from-scratch.ipynb)
+- [CNNs, Part 2](https://victorzhou.com/blog/intro-to-cnns-part-2/)
+- [CNNs, Part 1: An Introduction to Convolutional Neural Networks](https://victorzhou.com/blog/intro-to-cnns-part-1/)
+   - https://news.ycombinator.com/item?id=19981736
+- [Build a Neural Network](https://enlight.nyc/projects/neural-network)
+    - https://news.ycombinator.com/item?id=19870146
+- [Machine Learning for Beginners: An Introduction to Neural Networks](https://victorzhou.com/blog/intro-to-neural-networks/)
+- https://github.com/eriklindernoren/ML-From-Scratch
+  - https://news.ycombinator.com/item?id=13732288
+- [Live Coding Deep Learning Library - Joel Grus](https://github.com/joelgrus/joelnet)
+
+
+## Time Series
+
+- [ARIMA Model – Complete Guide to Time Series Forecasting in Python](https://www.machinelearningplus.com/time-series/arima-model-time-series-forecasting-python)
+  - https://news.ycombinator.com/item?id=20253622
+  - https://news.ycombinator.com/item?id=18794545
+  
+  
+## Support Vector Machines - SVM
+
+- https://www.svm-tutorial.com
+- http://web.mit.edu/6.034/wwwbob/svm-notes-long-08.pdf
+   - https://news.ycombinator.com/item?id=23368246
+   - https://news.ycombinator.com/item?id=18794545
+  
+## GANS
+
+- [Generative Adversarial Networks - The Story So Far](https://blog.floydhub.com/gans-story-so-far/)
+
+
+## Decision Trees
+
+- [ML from Scratch - Part 4: Decision Trees](http://www.oranlooney.com/post/ml-from-scratch-part-4-decision-tree/)
+- https://explained.ai/decision-tree-viz/index.html
+
+## Random Forests
+
+- [Random Forests for Complete Beginners](https://victorzhou.com/blog/intro-to-random-forests/)
+    - https://news.ycombinator.com/item?id=19632052
+
+
+## Back Propogation
+ 
+- http://people.idsia.ch/~juergen/who-invented-backpropagation.html
+- [Backpropogation is Just Steepest Descent with Automatic Differentiation](https://idontgetoutmuch.wordpress.com/2013/10/13/backpropogation-is-just-steepest-descent-with-automatic-differentiation-2/)
+    - https://news.ycombinator.com/item?id=19424813
+
+## Gradient Descent
+
+- [More Descent, Less Gradient](https://koaning.io/posts/more-descent-less-gradient/)
+   - https://news.ycombinator.com/item?id=23004026
+- [It’s Only Natural: An Excessively Deep Dive Into Natural Gradient Optimization](https://towardsdatascience.com/its-only-natural-an-excessively-deep-dive-into-natural-gradient-optimization-75d464b89dbb)
+- [Natural Gradient Descent](https://wiseodd.github.io/techblog/2018/03/14/natural-gradient/)
+- [An overview of gradient descent optimization algorithms](http://ruder.io/optimizing-gradient-descent/)
+
+## Reinforcement Learning
+
+- [A Brief Survey of Deep Reinforcement Learning](https://arxiv.org/pdf/1708.05866.pdf)
+- [Python Implementation of Reinforcement Learning: An Introduction](https://github.com/ShangtongZhang/reinforcement-learning-an-introduction)
+
+
+### Multi Arm Bandit
+
+- [Bayesian Bandits explained simply](https://towardsdatascience.com/bayesian-bandits-explained-simply-a5b43d9d5e38)
+- https://www.datahubbs.com/multi-armed-bandits-reinforcement-learning-2/
+- https://lilianweng.github.io/lil-log/2018/01/23/the-multi-armed-bandit-problem-and-its-solutions.html
+   - https://github.com/lilianweng/multi-armed-bandit
+- https://multithreaded.stitchfix.com/blog/2018/11/08/bandits/
+- http://ai.berkeley.edu/slides/
+- https://youtu.be/qAvY2tkMHHA
+- https://towardsdatascience.com/solving-the-multi-armed-bandit-problem-b72de40db97c
+   - https://github.com/ankonzoid/LearningX/tree/master/classical_RL/MAB
diff --git a/machine_learning.org b/machine_learning.org
deleted file mode 100644
index 4ec4f80..0000000
--- a/machine_learning.org
+++ /dev/null
@@ -1,16 +0,0 @@
-#+STARTUP: showall
-#+TITLE: Machine Learning
-#+AUTHOR: http://h4labs.com
-#+EMAIL: melling@h4labs.com
-
-* Inbox
-
-+ https://github.com/eriklindernoren/ML-From-Scratch
- - https://news.ycombinator.com/item?id=13732288
-+ http://bugra.github.io/work/notes/2014-08-23/on-machine-learning/
-+ [[https://news.ycombinator.com/item?id=10782909][Machine Learning - HN]]
-+ [[http://www.deeplearningbook.org][Deep Learning]] - Ian Goodfellow, Yoshua Bengio and Aaron Courville
- - https://news.ycombinator.com/item?id=11446164
-+ http://datanice.github.io/machine-learning-101-what-is-regularization-interactive.html
- - https://news.ycombinator.com/item?id=11906844
- 
diff --git a/math.md b/math.md
new file mode 100644
index 0000000..ce89251
--- /dev/null
+++ b/math.md
@@ -0,0 +1,158 @@
+# Math
+
+## Inbox
+
+- [Map of Mathematics](https://www.quantamagazine.org/the-map-of-mathematics-20200213/)
+   - https://news.ycombinator.com/item?id=22328516
+- [Geometric Algebra - Video](https://youtu.be/tX4H_ctggYo)
+   - https://news.ycombinator.com/item?id=22282452
+- https://www.maths.cam.ac.uk/documents/reading-list.pdf/
+- [The Matrix Calculus You Need For Deep Learning](https://explained.ai/matrix-calculus/index.html)
+   - https://news.ycombinator.com/item?id=21661545
+- [Matrix Cookbook](https://www.math.uwaterloo.ca/~hwolkowi/matrixcookbook.pdf)
+- [Ask HN: Are There Books for Mathematics Like Feynman's Lectures on Physics?](https://news.ycombinator.com/item?id=21346272)
+- [Gamedev Tutorial: Trigonometry Basics – Sine & Cosine](http://allenchou.net/2019/08/trigonometry-basics-sine-cosine/)
+  - https://news.ycombinator.com/item?id=20799024
+- [Introduction to Applied Linear Algebra – Vectors, Matrices, and Least Squares
+Stephen Boyd and Lieven Vandenberghe](https://web.stanford.edu/~boyd/vmls/)
+- [Calculus is Deeply Irrational](https://mathenchant.wordpress.com/2019/08/16/calculus-is-deeply-irrational/)
+   - https://news.ycombinator.com/item?id=20736277
+- http://www.feynmanlectures.caltech.edu/I_22.html
+   - https://news.ycombinator.com/item?id=20672605
+- [Curve Fitting](https://terpconnect.umd.edu/~toh/spectrum/CurveFitting.html)
+   - https://news.ycombinator.com/item?id=20609750
+- [Information Theory for Intelligent People](http://tuvalu.santafe.edu/~simon/it.pdf)
+   - https://news.ycombinator.com/item?id=20611270
+- [What is (Gaussian) curvature?](https://bastian.rieck.me/blog/posts/2019/curvature/)
+   - https://news.ycombinator.com/item?id=20546527
+- [A Mathematician's Apology](https://en.m.wikipedia.org/wiki/A_Mathematician's_Apology)
+   - https://archive.org/details/hardy_annotated/page/n1
+- [A Mathematician’s Lament](https://www.maa.org/external_archive/devlin/LockhartsLament.pdf)
+- [Discrete Differential Geometry: An Applied Introduction](https://www.cs.cmu.edu/~kmcrane/Projects/DGPDEC/paper.pdf)
+   - https://news.ycombinator.com/item?id=20542470
+- [Math Foundations: An Insight into Mathematics- 79 Videos](https://m.youtube.com/playlist?list=PL5A714C94D40392AB)
+- [Ask HN: Best way to relearn basic math?](https://news.ycombinator.com/item?id=20446796)
+- [Graphs and Geometry - Laszlo Lovasz](http://web.cs.elte.hu/~lovasz/bookxx/geomgraphbook/geombook2019.01.11.pdf)
+- [MIT 18.085 Computational Science](https://ocw.mit.edu/courses/mathematics/18-085-computational-science-and-engineering-i-fall-2008/)
+- [Foundations of Mathematics](http://www.mathetal.net/data/book1.pdf)
+   - https://news.ycombinator.com/item?id=20081573
+- [Discrete Mathematics and Functional Programming](https://cs.wheaton.edu/~tvandrun/dmfp/)
+- [Siraj Raval Links to Several Math Cheatsheets](https://github.com/llSourcell/Mathematics_for_Beginners/blob/master/README.md)
+- [Mathematics Cheat Sheet](https://ourway.keybase.pub/mathematics_cheat_sheet.pdf)
+   - https://news.ycombinator.com/item?id=20048205
+- [Set Theory and Foundations of Mathematics](http://settheory.net/)
+   - https://news.ycombinator.com/item?id=19967982
+- [Self Studying the MIT Applied Math Curriculum](https://www.harshsikka.me/self-studying-the-mit-applied-math-curriculum/)
+    - https://news.ycombinator.com/item?id=19811715
+- [The 15 Most Famous Transcendental Numbers](http://sprott.physics.wisc.edu/Pickover/trans.html)
+- [Viewing Matrices & Probability as Graphs](https://www.math3ma.com/blog/matrices-probability-graphs)
+    - https://news.ycombinator.com/item?id=19323123
+- http://tutorial.math.lamar.edu/Classes/DE/Definitions.aspx
+    - https://news.ycombinator.com/item?id=18182425
+- [Finite Calculus: A Tutorial for Solving Nasty Sums](https://www.cs.purdue.edu/homes/dgleich/publications/Gleich%202005%20-%20finite%20calculus.pdf)
+- [Notes on Discrete Math - Yale](http://www.cs.yale.edu/homes/aspnes/classes/202/notes.pdf)
+    - https://news.ycombinator.com/item?id=17391580
+- [How to write math](https://news.ycombinator.com/item?id=16829440)
+- http://www.people.vcu.edu/~dcranston/490/handouts/math-read.html
+    - https://news.ycombinator.com/item?id=15905048
+- [HOW TO LEARN ADVANCED MATHEMATICS WITHOUT HEADING TO UNIVERSITY - PART 3](https://www.quantstart.com/articles/How-to-Learn-Advanced-Mathematics-Without-Heading-to-University-Part-3)
+    - https://news.ycombinator.com/item?id=12429349
+- [Paul's Online Math Notes](http://tutorial.math.lamar.edu)
+    - https://news.ycombinator.com/item?id=11469494
+- https://www.reddit.com/r/gamedev/comments/4525xs/understanding_2d_transformations_maths_for_gamedev/
+- https://gist.github.com/bishboria/8326b17bbd652f34566a - Graduate texts in mathematics
+- [Ask HN: A Good Book About Statistics?](http://news.ycombinator.com/item?id=10056789)
+    - http://news.ycombinator.com/item?id=10208861 The Math I Learned After I Thought Had Already Learned Math
+- http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
+- http://www.math.uah.edu/stat
+- [Calculus Learning Guide](http://betterexplained.com/guides/calculus/)
+   - https://news.ycombinator.com/item?id=11478368
+- [Chicago undergraduate mathematics bibliography](https://www.ocf.berkeley.edu/~abhishek/chicmath.htm)
+   - http://news.ycombinator.com/item?id=9927909
+- [Guide to Writing Mathematics](http://news.ycombinator.com/item?id=9715149)
+- http://jeremykun.com/2015/06/08/methods-of-proof-diagonalization
+- http://news.ycombinator.com/item?id=8348769 - How Not to Lie with Statistics: Avoiding Common Mistakes (1986) [pdf]
+- http://proofs.wiki/Main_Page
+- http://blog.circuitsofimagination.com/2015/02/15/Markov-Chains.html
+- http://news.ycombinator.com/item?id=9040051 - An Introduction to the Central Limit Theorem
+- http://www.countbayesie.com/blog/2015/2/21/variance-co-variance-and-correlation
+- http://web.mit.edu/18.06/www/videos.shtml
+- http://classmill.com/jennathompson/introduction-to-algebra
+- [Mathematics for Computer Science](http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-042j-mathematics-for-computer-science-fall-2010/video-lectures)
+
+## Books
+
+- [Advanced Algebra Textbooks - HN](https://news.ycombinator.com/item?id=10873471)
+- [Applied Mathematical Programming](http://web.mit.edu/15.053/www/)
+    - https://news.ycombinator.com/item?id=11848663
+
+## Linear Algebra
+
+- [MIT 18.06 - Gilbert Strang Fall 2011](https://ocw.mit.edu/courses/mathematics/18-06sc-linear-algebra-fall-2011/index.htm)
+  - [Spring 2010 - with videos](https://ocw.mit.edu/courses/mathematics/18-06-linear-algebra-spring-2010/)
+- [Relearning Matrices as Linear Functions](https://www.dhruvonmath.com/2018/12/31/matrices/)
+    - https://news.ycombinator.com/item?id=19730799
+- https://dhruvp.netlify.com/2018/12/31/matrices/
+- [3Blue1Brown](https://www.youtube.com/watch?v=fNk_zzaMoSs&list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
+- [An Intuitive Derivation of Eigenvectors](https://dhruvp.netlify.com/2019/02/25/eigenvectors/)
+- [Eigenvectors and Eigenvalues](http://setosa.io/ev/eigenvectors-and-eigenvalues/)
+- [The Essence of Linear Algebra](https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab)
+   - https://news.ycombinator.com/item?id=13051241
+   - https://news.ycombinator.com/item?id=13620871
+- http://jadagul.tumblr.com/post/145201618713/linear-programming-how-does-it-work
+   - https://news.ycombinator.com/item?id=11820512
+- http://nolaymanleftbehind.wordpress.com/2011/07/10/linear-algebra-what-matrices-actually-are
+- [Linear Algebra: What Matrices are](http://news.ycombinator.com/item?id=10139554)
+- [Interactive Linear Algebra](http://news.ycombinator.com/item?id=10183725)
+
+### Linear Algebra Books
+
+- [Linear Algebra - Jim Hefferon - Free](http://joshua.smcvt.edu/linearalgebra/)
+- [Linear Algebra - UC Davis - Free](https://www.math.ucdavis.edu/~linear/linear-guest.pdf)
+- [Linear Algebra Done Wrong - Free](https://www.math.brown.edu/~treil/papers/LADW/LADW.html)
+- [Linear Algebra Done Right](https://www.lesswrong.com/posts/BgEfvxBHPfHdaQxLH/insights-from-linear-algebra-done-right)
+
+## Bayes
+
+- [How to become a Bayesian in eight easy steps](https://osf.io/preprints/psyarxiv/ph6sw) 
+   - https://news.ycombinator.com/item?id=15031110
+- http://news.ycombinator.com/item?id=10529681
+- http://blog.rokkincat.com/machine-learning-bayes
+- http://allendowney.blogspot.com/2016/03/ive-been-busy-with-other-projects-so-i.html
+- https://www.countbayesie.com/blog/2016/5/1/a-guide-to-bayesian-statistics
+- http://allendowney.blogspot.com/2016/05/learning-to-love-bayesian-statistics.html
+
+## Markov Chains
+
+- [A Zero-Math Introduction to Markov Chain Monte Carlo Methods](https://towardsdatascience.com/a-zero-math-introduction-to-markov-chain-monte-carlo-methods-dcba889e0c50)
+   - https://news.ycombinator.com/item?id=15986687
+- [Markov Chains Explained Visually](http://setosa.io/ev/markov-chains/)
+   - https://news.ycombinator.com/item?id=11323122
+- http://ocw.mit.edu/courses/aeronautics-and-astronautics/16-410-principles-of-autonomy-and-decision-making-fall-2010/lecture-notes/MIT16_410F10_lec20.pdf
+   - https://news.ycombinator.com/item?id=11908890
+
+## Statistics
+
+- http://r-statistics.co/Statistical-Tests-in-R.html
+   - https://news.ycombinator.com/item?id=10821045
+- http://www.stat.cmu.edu/~larry/all-of-statistics/index.html
+   - https://news.ycombinator.com/item?id=11701020
+- http://students.brown.edu/seeing-theory/?vt=4
+  - https://news.ycombinator.com/item?id=13735714
+
+## Calculus
+
+- [Calculus - Gilbert Strang](https://www.freetechbooks.com/calculus-t1345.html)
+- [Calculus for Beginners and Artists](http://www-math.mit.edu/~djk/calculus_beginners/)
+   - https://news.ycombinator.com/item?id=20433533
+- [The Beauty of Calculus](https://frankeprogram.yale.edu/event/steven-strogatz-lecture-april-26-2019)
+   - https://news.ycombinator.com/item?id=19867401
+- [Big Picture of Calculus](https://www.youtube.com/watch?v=UcWsDwg1XwM&index=2&list=PLBE9407EA64E2C318)
+   - https://news.ycombinator.com/item?id=13634476
+- [Calculus Made Easy (1914)](http://djm.cc/library/Calculus_Made_Easy_Thompson.pdf)
+   - https://news.ycombinator.com/item?id=14161876
+   - [Gutenburg PDF](http://www.gutenberg.org/ebooks/33283)
+   - http://calculusmadeeasy.org/
+- [Herb Gross MIT Videos](https://www.youtube.com/playlist?list=PLW18-jILJ66t9KZvoPpN6bDQaP7Yg42Hh)
+- [MIT 18.01 Single Variable Calculus](https://ocw.mit.edu/courses/mathematics/18-01-single-variable-calculus-fall-2006/)
+- [MIT OCW Calculus List](https://ocw.mit.edu/courses/find-by-topic/#cat=mathematics&subcat=calculus)
diff --git a/math.org b/math.org
deleted file mode 100644
index 0aff283..0000000
--- a/math.org
+++ /dev/null
@@ -1,67 +0,0 @@
-#+STARTUP: showall
-#+TITLE: Math
-#+AUTHOR: http://h4labs.com
-#+EMAIL: melling@h4labs.com
-
-* Inbox
-+ http://www.people.vcu.edu/~dcranston/490/handouts/math-read.html
- - https://news.ycombinator.com/item?id=15905048
-+ [[https://www.quantstart.com/articles/How-to-Learn-Advanced-Mathematics-Without-Heading-to-University-Part-3][HOW TO LEARN ADVANCED MATHEMATICS WITHOUT HEADING TO UNIVERSITY - PART 3]]
- - https://news.ycombinator.com/item?id=12429349
-+ [[http://tutorial.math.lamar.edu][Paul's Online Math Notes]]
- - https://news.ycombinator.com/item?id=11469494
-+ https://www.reddit.com/r/gamedev/comments/4525xs/understanding_2d_transformations_maths_for_gamedev/
-+ https://gist.github.com/bishboria/8326b17bbd652f34566a - Graduate texts in mathematics
-+ [[http://news.ycombinator.com/item?id=10056789][Ask HN: A Good Book About Statistics?]]
-+ http://news.ycombinator.com/item?id=10208861 The Math I Learned After I Thought Had Already Learned Math
-+ http://camdavidsonpilon.github.io/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers
-+ http://www.math.uah.edu/stat
-+ [[http://betterexplained.com/guides/calculus/][Calculus Learning Guide]]
- - https://news.ycombinator.com/item?id=11478368
-
-* Books
-+ [[https://news.ycombinator.com/item?id=10873471][Advanced Algebra Textbooks - HN]]
-+ [[http://web.mit.edu/15.053/www/][Applied Mathematical Programming]]
- - https://news.ycombinator.com/item?id=11848663
-
-* Linear Algebra
-+ [[https://www.youtube.com/playlist?list=PLZHQObOWTQDPD3MizzM2xVFitgF8hE_ab][The Essence of Linear Algebra]]
- - https://news.ycombinator.com/item?id=13051241
- - https://news.ycombinator.com/item?id=13620871
-+ http://jadagul.tumblr.com/post/145201618713/linear-programming-how-does-it-work
- - https://news.ycombinator.com/item?id=11820512
-+ http://nolaymanleftbehind.wordpress.com/2011/07/10/linear-algebra-what-matrices-actually-are
-+ [[http://news.ycombinator.com/item?id=10139554][Linear Algebra: What Matrices are]] 
-+ [[http://news.ycombinator.com/item?id=10183725][Interactive Linear Algebra]]
-
-* Bayes
-+ [[https://osf.io/preprints/psyarxiv/ph6sw][How to become a Bayesian in eight easy steps]] 
- - https://news.ycombinator.com/item?id=15031110
-+ http://news.ycombinator.com/item?id=10529681
-+ http://blog.rokkincat.com/machine-learning-bayes
-+ http://allendowney.blogspot.com/2016/03/ive-been-busy-with-other-projects-so-i.html
-+ https://www.countbayesie.com/blog/2016/5/1/a-guide-to-bayesian-statistics
-+ http://allendowney.blogspot.com/2016/05/learning-to-love-bayesian-statistics.html
-
-* Markov Chains
-+ [[https://towardsdatascience.com/a-zero-math-introduction-to-markov-chain-monte-carlo-methods-dcba889e0c50][A Zero-Math Introduction to Markov Chain Monte Carlo Methods]]
- - https://news.ycombinator.com/item?id=15986687
-+ [[http://setosa.io/ev/markov-chains/][Markov Chains Explained Visually]]
- - https://news.ycombinator.com/item?id=11323122
-+ http://ocw.mit.edu/courses/aeronautics-and-astronautics/16-410-principles-of-autonomy-and-decision-making-fall-2010/lecture-notes/MIT16_410F10_lec20.pdf
- - https://news.ycombinator.com/item?id=11908890
-
-* Statistics
-+ http://r-statistics.co/Statistical-Tests-in-R.html
- - https://news.ycombinator.com/item?id=10821045
-+ http://www.stat.cmu.edu/~larry/all-of-statistics/index.html
- - https://news.ycombinator.com/item?id=11701020
-+ http://students.brown.edu/seeing-theory/?vt=4
- - https://news.ycombinator.com/item?id=13735714
-
-* Calculus
-+ [[https://www.youtube.com/watch?v=UcWsDwg1XwM&index=2&list=PLBE9407EA64E2C318][Big Picture of Calculus]]
- - https://news.ycombinator.com/item?id=13634476
-+  [[http://djm.cc/library/Calculus_Made_Easy_Thompson.pdf][Calculus Made Easy (1914)]]
- - https://news.ycombinator.com/item?id=14161876
- 
diff --git a/physics.md b/physics.md
new file mode 100644
index 0000000..bb03bf4
--- /dev/null
+++ b/physics.md
@@ -0,0 +1,20 @@
+
+# Physics
+
+
+## Inbox
+
+- [PhD LIVE](https://www.youtube.com/watch?v=2dKxR313yfw)
+- http://www.feynmanlectures.caltech.edu/II_19.html
+   - https://news.ycombinator.com/item?id=20694173
+- [Learn_Physics_in_2_Months](https://github.com/llSourcell/Learn_Physics_in_2_Months)
+- http://theoreticalminimum.com/courses
+- [The Feynman Lectures on Physics, Volume III](http://www.feynmanlectures.caltech.edu/III_toc.html)
+- https://news.ycombinator.com/item?id=11216668 HN - Best Way to Learn Physics?
+- [So You Want To Learn Physics...](http://www.susanjfowler.com/blog/2016/8/13/so-you-want-to-learn-physics)
+  - https://news.ycombinator.com/item?id=12691963
+  - https://news.ycombinator.com/item?id=13684303
+  - https://news.ycombinator.com/item?id=18374994
+- [Mathematics for Physics](http://www.goldbart.gatech.edu/PostScript/MS_PG_book/bookmaster.pdf)
+  - https://news.ycombinator.com/item?id=14459150
+  
diff --git a/physics.org b/physics.org
deleted file mode 100644
index 50d315c..0000000
--- a/physics.org
+++ /dev/null
@@ -1,15 +0,0 @@
-#+STARTUP: showall
-#+TITLE: Physics
-#+AUTHOR: http://h4labs.com
-#+EMAIL: melling@h4labs.com
-
-* Inbox
-+ http://theoreticalminimum.com/courses
-+ [[http://www.feynmanlectures.caltech.edu/III_toc.html][The Feynman Lectures on Physics, Volume III]]
-+ https://news.ycombinator.com/item?id=11216668 HN - Best Way to Learn Physics?
-+ [[http://www.susanjfowler.com/blog/2016/8/13/so-you-want-to-learn-physics][So You Want To Learn Physics...]]
- - https://news.ycombinator.com/item?id=12691963
- - https://news.ycombinator.com/item?id=13684303
-+ [[http://www.goldbart.gatech.edu/PostScript/MS_PG_book/bookmaster.pdf][Mathematics for Physics]]
- - https://news.ycombinator.com/item?id=14459150
-  
diff --git a/quant_trading.md b/quant_trading.md
index 107e860..fe38d28 100644
--- a/quant_trading.md
+++ b/quant_trading.md
@@ -3,6 +3,9 @@
 
 
 ## Inbox
+
+- https://github.com/cantaro86/Financial-Models-Numerical-Methods
+- http://archive.nytimes.com/www.nytimes.com/interactive/2011/01/02/business/20110102-metrics-graphic.html
 - https://blog.headlandstech.com/2017/08/03/quantitative-trading-summary/
     - https://news.ycombinator.com/item?id=16196421
 - https://dailycodingproblem.com/blog/2018/01/02/find-an-arbitrage.html
@@ -16,5 +19,7 @@
   - https://news.ycombinator.com/item?id=11887147
 -  http://www.scientificamerican.com/article/multifractals-explain-wall-street/
    - https://news.ycombinator.com/item?id=417463
+- https://www.reddit.com/r/algotrading/comments/cr7jey/ive_reproduced_130_research_papers_about/
+   - https://news.ycombinator.com/item?id=20720095
 
 ## Present Value
diff --git a/statistics/README.md b/statistics/README.md
index 92853de..55fa2b3 100644
--- a/statistics/README.md
+++ b/statistics/README.md
@@ -1,11 +1,47 @@
-# Statistics
+# Probability and Statistics
 
-## INBOX
+## Inbox
+
+- https://lambdaclass.com/data_etudes/central_limit_theorem_misuse/
+- [The Little Handbook of Statistical Practice](http://www.jerrydallal.com/LHSP/LHSP.htm)
+   - https://news.ycombinator.com/item?id=21382470
+- Monty Hall Problem
+   - https://news.ycombinator.com/item?id=21348476
+- [Gaussian Processes, not quite for dummies](https://yugeten.github.io/posts/2019/09/GP/)
+   - https://news.ycombinator.com/item?id=20977087
+- [Data Science. The Central Limit Theorem and sampling](https://luminousmen.com/post/data-science-central-limit-theorem)
+- [German Tank Problem](https://www.eadan.net/blog/german-tank-problem/)
+   - https://news.ycombinator.com/item?id=20318184
+- [Probability Theory Lectures by Aubrey Clayton](https://m.youtube.com/playlist?list=PL9v9IXDsJkktefQzX39wC2YG07vw7DsQ_)
+- [Statistical Modeling: The Two Cultures](https://projecteuclid.org/download/pdf_1/euclid.ss/1009213726)
+    - https://news.ycombinator.com/item?id=19835962
+- [Some intuition behind random walks](https://github.com/joseprupi/randomwalk)
+- https://99percentinvisible.org/episode/on-average/
+    - You can design for the average and not fit anyone.
+- [The ‘Hot Hand’ Debate Gets Flipped on Its Head](https://www.wsj.com/articles/the-hot-hand-debate-gets-flipped-on-its-head-1443465711)
+    - https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2627354&mod=article_inline
+    - https://www.bloomberg.com/news/audio/2019-03-28/joshua-miller-discusses-the-hot-hand-phenomenon-podcast
+- [Common statistical tests are linear models (or: how to teach stats)](https://lindeloev.github.io/tests-as-linear/)
+    - https://news.ycombinator.com/item?id=19511420
+- [Probability Theory (For Scientists and Engineers)
+](https://betanalpha.github.io/assets/case_studies/probability_theory.html)
+   - https://news.ycombinator.com/item?id=16841747
+- https://theclevermachine.wordpress.com/2012/11/19/a-gentle-introduction-to-markov-chain-monte-carlo-mcmc/
+   - https://theclevermachine.wordpress.com/2012/09/22/monte-carlo-approximations/
+   - https://theclevermachine.wordpress.com/2012/09/24/a-brief-introduction-to-markov-chains/
+   - https://theclevermachine.wordpress.com/2012/10/05/mcmc-the-metropolis-sampler/
+   - https://theclevermachine.wordpress.com/2012/10/20/mcmc-the-metropolis-hastings-sampler/
+   - 
+- [Conditional probability - A Visual explanation by Victor Powell](http://setosa.io/conditional/)
+- [Seeing Theory](https://seeing-theory.brown.edu/index.html)
 
 ## Courses
+
 - [Harvard Stats 110](https://projects.iq.harvard.edu/stat110/home) | [YouTube](https://projects.iq.harvard.edu/stat110/youtube) | [Max Wang Class Notes](http://www.mxawng.com/stuff/notes/stat110.pdf) | [William Chen Cheatsheet](http://www.wzchen.com/probability-cheatsheet)
   - [Top 10 Ideas from Class](https://www.quora.com/What-are-the-top-10-big-ideas-in-Statistics-110-Introduction-to-Probability-at-Harvard)
-- [MIT]
+- [MIT 6.041/6.431 - Prof. John Tsitsiklis Fall 2010 with videos](https://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-041-probabilistic-systems-analysis-and-applied-probability-fall-2010/)
+- [MIT 18.650 Statistics for Applications - Fall 2016](https://ocw.mit.edu/courses/mathematics/18-650-statistics-for-applications-fall-2016/index.htm)
+- [MIT 18.440](https://ocw.mit.edu/courses/mathematics/18-440-probability-and-random-variables-spring-2014/)
 - [Notre Dame](https://youtu.be/YTBFSmExXRc)
 - [Stanford CS109](https://web.stanford.edu/class/archive/cs/cs109/cs109.1166//handouts/overview.html)
 - [UC Irvine Stats 131a](http://ocw.uci.edu/courses/math_131a_introduction_to_probability_and_statistics.html)
@@ -17,12 +53,45 @@
 
 
 ## Online Books
+
+- [All of Statistics by Larry Wasserman](https://www.stat.cmu.edu/~larry/all-of-statistics/)
+- https://probabilitycourse.com/
 - [Introduction to Probability and Statistics Using R](https://cran.r-project.org/web/packages/IPSUR/vignettes/IPSUR.pdf)
 - [Probability and Stochastic Processes with Applications - Oliver Knill](http://www.math.harvard.edu/~knill/teaching/math144_1994/probability.pdf)
 
 ## Blogs
+
 - https://blog.statsbot.co
+- https://jontysinai.github.io/jekyll/update/2017/11/23/probability-for-everyone.html
+- https://jontysinai.github.io/jekyll/update/2018/12/23/probability-part-two-conditional-probability.html
 
 ## Bayes
+
 - http://www.greenteapress.com/thinkbayes/html/thinkbayes001.html
   - https://news.ycombinator.com/item?id=15732926
+- https://gfrison.com/2019/statistical-puzzle-bayesian-conditioning
+
+## Maximum Likelihood Estimation - MLE
+
+- [Maximum Likelihood Estimationmin R](https://youtu.be/w3drLH-DFpE)
+
+## Markov Chains
+
+- https://news.ycombinator.com/item?id=19633212
+- [Introduction to Markov Chains](https://towardsdatascience.com/introduction-to-markov-chains-50da3645a50d)
+- [The Markov Property, Chain, Reward Process and Decision Process](https://xaviergeerinck.com/markov-property-chain-reward-decision)
+    - https://news.ycombinator.com/item?id=17112302
+
+## Kalman Filters
+
+- [How a Kalman filter works, in pictures ](http://www.bzarg.com/p/how-a-kalman-filter-works-in-pictures/)
+`   - https://news.ycombinator.com/item?id=17116149
+    - https://news.ycombinator.com/item?id=10042050
+    - https://news.ycombinator.com/item?id=13449229
+- http://www.anuncommonlab.com/articles/how-kalman-filters-work/
+    - https://news.ycombinator.com/item?id=11561770
+- https://github.com/lukstei/trading-backtest/tree/master
+- http://htmlpreview.github.io/?https://github.com/aguaviva/KalmanFilter/blob/master/KalmanFilter.html
+    - https://news.ycombinator.com/item?id=16575679
+- 
+