Update README.md

Author: krzjoa

README.md

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 ## Model Explanation
 
-* [dalex](https://github.com/ModelOriented/DALEX) - moDel Agnostic Language for Exploration and eXplanation.
+* [dalex](https://github.com/ModelOriented/DALEX) - moDel Agnostic Language for Exploration and eXplanation. img height="20" src="img/sklearn_big.png" alt="sklearn"><img height="20" src="img/R_big.png" alt="R inspired/ported lib">
 * [Shapley](https://github.com/benedekrozemberczki/shapley) - A data-driven framework to quantify the value of classifiers in a machine learning ensemble. 
 * [Alibi](https://github.com/SeldonIO/alibi) - Algorithms for monitoring and explaining machine learning models.
 * [anchor](https://github.com/marcotcr/anchor) - Code for "High-Precision Model-Agnostic Explanations" paper.
@@ -278,7 +278,6 @@
 * [FairML](https://github.com/adebayoj/fairml) - FairML is a python toolbox auditing the machine learning models for bias. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [L2X](https://github.com/Jianbo-Lab/L2X) - Code for replicating the experiments in the paper *Learning to Explain: An Information-Theoretic Perspective on Model Interpretation*.
 * [PDPbox](https://github.com/SauceCat/PDPbox) - Partial dependence plot toolbox.
-* [pyBreakDown](https://github.com/MI2DataLab/pyBreakDown) - Python implementation of R package breakDown. <img height="20" src="img/sklearn_big.png" alt="sklearn"><img height="20" src="img/R_big.png" alt="R inspired/ported lib">
 * [PyCEbox](https://github.com/AustinRochford/PyCEbox) - Python Individual Conditional Expectation Plot Toolbox.
 * [Skater](https://github.com/datascienceinc/Skater) - Python Library for Model Interpretation.
 * [model-analysis](https://github.com/tensorflow/model-analysis) - Model analysis tools for TensorFlow. <img height="20" src="img/tf_big2.png" alt="sklearn">
@@ -423,12 +422,16 @@
 * [Distributed](https://github.com/dask/distributed) - Distributed computation in Python.
 
 ## Experimentation
+* [mlflow](https://github.com/mlflow/mlflow) - Open source platform for the machine learning lifecycle.
+* [Neptune](https://neptune.ai) - A lightweight ML experiment tracking, results visualization and management tool.
+* [dvc](https://github.com/iterative/dvc) - Data Version Control | Git for Data & Models | ML Experiments Management.
 * [envd](https://github.com/tensorchord/envd) - 🏕️ machine learning development environment for data science and AI/ML engineering teams.
 * [Sacred](https://github.com/IDSIA/sacred) - A tool to help you configure, organize, log and reproduce experiments.
 * [Xcessiv](https://github.com/reiinakano/xcessiv) - A web-based application for quick, scalable, and automated hyperparameter tuning and stacked ensembling.
 * [Persimmon](https://github.com/AlvarBer/Persimmon) - A visual dataflow programming language for sklearn.
-* [Ax](https://github.com/facebook/Ax) - Adaptive Experimentation Platform. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [Neptune](https://neptune.ai) - A lightweight ML experiment tracking, results visualization and management tool.
+* [Ax](https://github.com/facebook/Ax) - Adaptive Experimentation Platform. <img height="20" src="img/sklearn_big.png" alt="sklearn">
+
 
 ## Evaluation
 * [recmetrics](https://github.com/statisticianinstilettos/recmetrics) - Library of useful metrics and plots for evaluating recommender systems.