这本书是介绍深度强化学习的,使用python,非常新,2020年出版的,761页,github有代码,貌似没有中文版。 介绍深度学习的书籍有很多,比如Richard Shutton的Reinforcement Learning, An Introduction, 2nd editio…
Source Code for the book "Deep Reinforcement Learning with Python", second edition by Nimish Sanghi Local Install - Ubuntu and Windows WSL2 Please install following ubuntu packages using: apt-get install swig cmake ffmpeg freeglut3-dev xvfb git-lfs git lfs install Create a new venv or con...
深度学习的大众化:Theano 和 tensorflow是两个符号式的张量运算的python框架,都支持自动求微分。Keras等用户友好型库则使深度学习变得像操作乐高积木一样简单。
Chapter 1: Getting Started with Deep Learning Using PyTorch Chapter 2: Building Blocks of Neural Networks Section 2: Going Advanced with Deep Learning Chapter 3: Diving Deep into Neural Networks Chapter 4: Deep Learning for Computer Vision Chapter 5: Natural Language Processing with Sequence Data S...
Master classic RL, deep RL, distributional RL, inverse RL, and more with OpenAI Gym and TensorFlow. 20 customer reviews. Instant delivery. Top rated Programming products.
经典书籍:Reinforcement Learning: An Introduction (2nd Edition) 论文集,覆盖面比较广,需要一定基础:Reinforcement Learning: State-of-the-Art 两个非常全的论文资料集合: GitHub - junhyukoh/deep-reinforcement-learning-papers: A list of recent papers regarding deep reinforcement learning ...
经典书籍:Reinforcement Learning: An Introduction (2nd Edition) 论文集,覆盖面比较广,需要一定基础:Reinforcement Learning: State-of-the-Art 两个非常全的论文资料集合: GitHub - junhyukoh/deep-reinforcement-learning-papers: A list of recent papers regarding deep reinforcement learning ...
Chapter 1: Introduction to Deeep Reinforcement Learning 📜 ARTICLE Introduction to Deep Reinforcement Learning 📹 VIDEO Introduction to Deep Reinforcement Learning Chapter 2: Q-learning with Taxi-v3 🚕 📜 ARTICLE: Q-Learning, let’s create an autonomous Taxi 🚖 (Part 1/2) VIDEO Q-Lear...
Deep reinforcement learning augments the reinforcement learning framework and utilizes the powerful representation of deep neural networks. Recent works ha
Maxim has been working as a software developer for more than 20 years and was involved in various areas: distributed scientific computing, distributed systems and big data processing. Since 2014 he is actively using machine and deep learning to solve practical industrial tasks, such as NLP problems...