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ShaneHX
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🦜🔗 Build context-aware reasoning applications
aka "Bayesian Methods for Hackers": An introduction to Bayesian methods + probabilistic programming with a computation/understanding-first, mathematics-second point of view. All in pure Python ;)
Implementation of Reinforcement Learning Algorithms. Python, OpenAI Gym, Tensorflow. Exercises and Solutions to accompany Sutton's Book and David Silver's course.
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filte…
A collection of various deep learning architectures, models, and tips
Interview = 简历指南 + 算法题 + 八股文 + 源码分析
A course in reinforcement learning in the wild
Pytorch🍊🍉 is delicious, just eat it! 😋😋
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
Simplified implementations of deep learning related works
EPFL Course - Optimization for Machine Learning - CS-439
Coursera Open Courses from University of Toronto
Jupyter notebooks and other materials developed for the Columbia course APMA 4300