PacktPublishing / Large-Scale-Machine-Learning-With-PythonLinks
Code repository for Large Scale Machine Learning with Python, published by Packt
☆90Updated 2 years ago
Alternatives and similar repositories for Large-Scale-Machine-Learning-With-Python
Users that are interested in Large-Scale-Machine-Learning-With-Python are comparing it to the libraries listed below
Sorting:
- Some work on Kaggle data for fun☆64Updated 7 years ago
- Code for the Kaggle acquire valued shoppers challenge☆66Updated 11 years ago
- Containing codes of participation in Kaggle competitions.☆37Updated 9 years ago
- Code Repository for Python Deeper Insights into Machine Learning, published by packt☆30Updated 2 years ago
- Code snippets for "Introduction to Deep Learning with TensorFlow" at PyData Ann Arbor Aug 2017☆80Updated 7 years ago
- Code files added☆99Updated 2 years ago
- Companion code for my video course on Practical Python Data Science Techniques, published by Packt Publishing☆33Updated 7 years ago
- My winning solution for Kaggle Higgs Machine Learning Challenge (single classifier, xgboost)☆82Updated 10 years ago
- This library is a wrapper for sklearn and works with data stored using Pandas module.☆17Updated 9 years ago
- ☆66Updated 2 years ago
- Advanced Scikit-learn training session☆118Updated 9 years ago
- environment setup for strata conference 2018☆67Updated 7 years ago
- Code for O'Reilly's "A Short Course on TensorFlow"☆104Updated 8 years ago
- Tutorial Created for SciPy 2012☆58Updated 12 years ago
- A Little Book of Python for Multivariate Analysis☆87Updated 9 years ago
- Various notebooks and tutorials on subjects of interest.☆36Updated 5 years ago
- Tutorial on deploying machine learning models to production☆59Updated 5 years ago
- Jupyter Notebooks for Strata Data Conference NY 2017 Deep Learning for Recommender Systems Tutorial☆22Updated 7 years ago
- How to predict credit defaulting?☆93Updated 5 years ago
- Some thoughts on how to use machine learning in production☆72Updated 8 years ago
- Solution code from my winning submission to Kaggle's PyCon 2015 competition☆55Updated 10 years ago
- Lecture notes on probabilistic graphical modeling, based on Stanford CS228 (work in progress!)☆30Updated 8 years ago
- Course of Machine Learning in Science and Industry at Heidelberg university☆47Updated 8 years ago
- COMS W4995 Applied Machine Learning - Spring 18☆157Updated 6 years ago
- 32/2384 Solution to Kaggle Mercari Competition (solo silver medal winner)☆21Updated 7 years ago
- Practical Reinforcement Learning, published by Packt☆25Updated 2 years ago
- 2nd Place Solution of the Kaggle Competition - Santander Product Recommendation☆176Updated 3 years ago
- Materials for the "Advanced Scikit-learn" class in the afternoon☆165Updated 6 years ago
- Source code for 'Practical Machine Learning with Python' by Dipanjan Sarkar, Raghav Bali, and Tushar Sharma☆123Updated 7 years ago
- ☆26Updated 9 years ago