amueller / COMS4995-s19Links
COMS W4995 Applied Machine Learning - Spring 19
☆302Updated 5 years ago
Alternatives and similar repositories for COMS4995-s19
Users that are interested in COMS4995-s19 are comparing it to the libraries listed below
Sorting:
- COMS W4995 Applied Machine Learning - Spring 18☆158Updated 6 years ago
- Jupyter notebooks for summarizing and reproducing the textbook "The Elements of Statistical Learning" 2/E by Hastie, Tibshirani, and Frie…☆288Updated 7 years ago
- COMS W4995 Applied Machine Learning - Spring 20☆247Updated 3 years ago
- Materials for GWU DNSC 6279 and DNSC 6290.☆239Updated 3 weeks ago
- Introduction to Machine learning with Python, 4h interactive workshop☆311Updated 5 years ago
- Advanced Machine Learning with Scikit-learn part II☆163Updated 5 years ago
- Automated feature engineering in Python with Featuretools☆518Updated 6 years ago
- Advanced Machine Learning with Scikit-learn part I☆141Updated 5 years ago
- Python script to pull machine learning flashcards from Chris Albon's twitter feed☆81Updated 6 years ago
- Tutorials on visualizing data using python packages like bokeh, plotly, seaborn and igraph☆267Updated 5 years ago
- Automated vs Manual Feature Engineering Comparison. Implemented using Featuretools.☆327Updated 4 years ago
- Feature Engineering Made Easy, published by Packt☆216Updated 2 years ago
- Created the contents of this repo originally for a workshop I gave at UCLA☆113Updated 5 years ago
- ☆108Updated 3 years ago
- Resources for the PyCon 2017 tutorial, "Exploratory data analysis in python"☆236Updated 2 years ago
- Intermediate Machine Learning with Scikit-learn, 4h interactive workshop☆127Updated 4 years ago
- Scipy 2018 scikit-learn tutorial by Guillaume Lemaitre and Andreas Mueller☆248Updated 6 years ago
- ☆85Updated 7 years ago
- Project work for Udacity's AB Testing Course☆82Updated 8 years ago
- A collection of notebook to learn the Applied Predictive Modeling using Python.☆275Updated 8 years ago
- Basics of programming: algorithms, data structures, object oriented programming☆93Updated 7 years ago
- How to Win a Data Science Competition: Learn from Top Kagglers☆175Updated 7 years ago
- Statistics for Machine Learning, published by Packt☆155Updated 2 years ago
- Materials for an online-course - "Practical XGBoost in Python"☆220Updated 8 years ago
- Course material for STAT 479: Machine Learning (FS 2018) at University Wisconsin-Madison☆493Updated 6 years ago
- A compiled list of kaggle competitions and their winning solutions for classification problems.☆270Updated 8 years ago
- PyParis tutorial on machine learning using scikit-learn☆74Updated last year
- Course notes for MSDS501, computational boot camp, at the University of San Francisco☆124Updated 3 years ago
- Materials for the "Advanced Scikit-learn" class in the afternoon☆165Updated 6 years ago
- Machine Learning and Data Analysis Case Studies using Spark.☆72Updated 4 years ago