My Reading Lists of Deep Learning and Natural Language Processing
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Updated
Apr 30, 2022 - TeX
My Reading Lists of Deep Learning and Natural Language Processing
RL Notation and Pseudocode for Udacity's MLND program
Reinforcement learning theory book about foundations of deep RL algorithms with proofs.
Hierarchical Bayesian modeling of RLDM tasks, using R & Python
Reinforcement Learning Cheat Sheet
Collection of lectures and lab lectures on machine learning and deep learning. Lab practices in Python and TensorFlow.
Modeling agents with probabilistic programs
Cheatsheet of Reinforcement Learning (Based on Sutton-Barto Book - 2nd Edition)
I have created a small book summarizing concepts from the Reinforcement Learning part of the ATML 2015 course at UCL (https://www.davidsilver.uk/teaching/)
Deep Reinforcement Learning in Autonomous Driving: the A3C algorithm used to make a car learn to drive in TORCS; Python 3.5, Tensorflow, tensorboard, numpy, gym-torcs, ubuntu, latex
Notes and solutions to exercises in Sutton and Barto's Reinforcement Learning textbook
Simulation based Soft Continuum Robot Control via Reinforcement Learning
Unified notation for Markov Decision Processes PO(MDP)s
A summary of important concepts and algorithms in RL
🐲 Stanford CS234 : Reinforcement Learning
Multi-agent reinforcement learning on trains, for Deep Learning class at UNIBO
Use RL to balance the electrical power grid with electric vehicle fleets
Samson's MIT Master's Degree Thesis: "Multi-Agent Deep Reinforcement Learning and GAN-Based Market Simulation for Derivatives Pricing and Dynamic Hedging".
Solutions to Sutton and Barto book exercises
A list of various articles that I find helpful for reading about deep learning, forecasting, or macroeconomics
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