No-Stream
Follow
Stars
A scikit-learn-compatible Python implementation of ReBATE, a suite of Relief-based feature selection algorithms for Machine Learning.
A library of sklearn compatible categorical variable encoders
Automated Machine Learning with scikit-learn
Python implementations of the Boruta all-relevant feature selection method.
[CONTRIBUTORS WELCOME] Generalized Additive Models in Python
Implementation of deep learning models for time series in PyTorch.
vtreat is a data frame processor/conditioner that prepares real-world data for predictive modeling in a statistically sound manner. Distributed under a BSD-3-Clause license.
PyTorch implementation of the NIPS-17 paper "Poincaré Embeddings for Learning Hierarchical Representations"
Experiments with Deep Learning
This repository contains a notebook demonstrating a practical implementation of the so-called Entity Embedding for Encoding Categorical Features for Training a Neural Network.
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Data, Benchmarks, and methods submitted to the M4 forecasting competition
1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.
A system for quickly generating training data with weak supervision
pymc-learn: Practical probabilistic machine learning in Python
(OLD REPO) Line-by-line profiling for Python - Current repo ->
Magenta: Music and Art Generation with Machine Intelligence
Music generation with Keras and LSTM
A Python toolbox for gaining geometric insights into high-dimensional data
A game theoretic approach to explain the output of any machine learning model.
A helping hand for generating sensible data with ScalaCheck
Lightweight, modular, and extensible library for functional programming.
Apache Spark testing helpers (dependency free & works with Scalatest, uTest, and MUnit)
A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
Jupyter meets Vim. Vimmer will fall in love.