Stars
A game theoretic approach to explain the output of any machine learning model.
Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media
YSDA course in Natural Language Processing
A Python Automated Machine Learning tool that optimizes machine learning pipelines using genetic programming.
Notebooks and code for the book "Introduction to Machine Learning with Python"
The "Python Machine Learning (2nd edition)" book code repository and info resource
A collection of tutorials and examples for solving and understanding machine learning and pattern classification tasks
Jupyter notebooks from the scikit-learn video series
Lectures on scientific computing with python, as IPython notebooks.
Debugging, monitoring and visualization for Python Machine Learning and Data Science
Repository for "Introduction to Artificial Neural Networks and Deep Learning: A Practical Guide with Applications in Python"
Jupyter notebook and datasets from the pandas video series
Beyond Accuracy: Behavioral Testing of NLP models with CheckList
Code, Notebooks and Examples from Practical Business Python
General Assembly's 2015 Data Science course in Washington, DC
Advanced Statistical Computing at Vanderbilt University Medical Center's Department of Biostatistics
Machine Learning with Text in scikit-learn
Tutorial: Bayesian Statistical Analysis in Python
Apache Spark (PySpark) Practice on Real Data
Step-by-step Deep Leaning Tutorials on Apache Spark using BigDL
Apache Spark (Scala, PySpark, SparkR) Code, Tricks, and References
This is where all of the IPython Notebooks will be kept from the blog
scikit-learn course for 2017 NGCM Summer Academy
This is repository, which contains the "Machine Learning Applications of Big Data" supplementary materials on Coursera
Tensorflow Basic tutorials