DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning-master资源-CSDN文库

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《DeepMind高级深度学习与强化学习精粹》在当今的AI领域，深度学习和强化学习无疑是两大核心技术，尤其在谷歌旗下的DeepMind公司，这两者得到了深入的研究与应用。本资料集“DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning-master”是DeepMind与伦敦大学学院（UCL）合作的课程内容，旨在引领学者探索深度学习的奥秘以及强化学习的实战策略。深度学习，作为机器学习的一个分支，通过构建多层神经网络来模拟人脑的学习过程，实现对复杂数据模式的自动识别和学习。在这个课程中，我们将深入讨论深度神经网络（DNN）、卷积神经网络（CNN）和循环神经网络（RNN），以及它们在图像识别、语音处理和自然语言理解等领域的应用。此外，我们还将探讨更先进的技术，如自编码器（Autoencoder）、生成对抗网络（GANs）和变分自编码器（VAEs），这些都是深度学习在无监督学习和生成任务中的关键工具。强化学习则是一种通过与环境互动来学习最优决策策略的方法，其核心是通过试错学习，不断优化策略以获得最大奖励。在DeepMind的实践中，强化学习成功地应用于AlphaGo，击败了世界围棋冠军。本课程将介绍Q-learning、SARSA、Deep Q-Networks（DQN）等强化学习算法，并讨论它们在游戏、机器人控制、资源管理等领域的应用。此外，我们还将深入探讨近期的进展，如蒙特卡洛树搜索（MCTS）和模型预测控制（Model Predictive Control）在强化学习中的应用。此资料集包含的文件很可能是课程的源代码、讲义、实验指导和论文阅读材料，为学习者提供了丰富的实践和理论基础。通过这些资源，学习者不仅可以掌握深度学习和强化学习的基本原理，还能了解最新的研究动态，甚至参与到实际项目中，提升解决复杂问题的能力。 “DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning-master”是一个全面而深入的教程，涵盖了深度学习和强化学习的各个方面，适合有一定编程基础并希望在AI领域深造的学者。通过系统学习，你可以成为一名能够应对各种挑战的AI专家，掌握改变未来的技术。

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DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning-master.zip （17个子文件）

DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning-master

README.md 6KB

lecture slides

rl_03 Markov Decision Processes and Dynamic Programming.pdf 1.1MB

dl_01 Introduction to Machine Learning Based AI.pdf 7.39MB

rl_06 Policy Gradients and Actor Critics.pdf 677KB

rl_05 Function Approximation and Deep Reinforcement Learning.pdf 1.81MB

dl_07 Attention and Memory in Deep Learning.pdf 3.88MB

rl_01 Introduction to Reinforcement Learning.pdf 2.02MB

rl_04 Model-Free Prediction and Control.pdf 1.28MB

rl_08 Advanced Topics in Deep RL.pdf 691KB

dl_08 Unsupervised learning and generative models.pdf 24.44MB

dl_03 Neural Networks Foundations.pdf 2.36MB

dl_05 Optimization for Machine Learning.pdf 3.01MB

dl_02 Introduction to TensorFlow.pdf 1.05MB

rl_02 Exploration and Exploitation.pdf 860KB

dl_04 Beyond Image Recognition, End-to-End Learning, Embeddings.pdf 5.01MB

dl_06 Deep Learning for NLP.pdf 3.54MB

rl_07 Planning and Models.pdf 1.92MB

# Advanced Deep Learning and Reinforcement Learning ##### Advanced Deep Learning and Reinforcement Learning course taught at [UCL](http://www.cs.ucl.ac.uk/current_students/syllabus/compgi/compgi22_advanced_deep_learning_and_reinforcement_learning/) in partnership with [DeepMind](https://deepmind.com) ### Deep Learning 1: Introduction to Machine Learning Based AI [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_01%20Introduction%20to%20Machine%20Learning%20Based%20AI.pdf) [[video]](https://www.youtube.com/watch?v=iOh7QUZGyiU&t=0s&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=2) ### Deep Learning 2: Introduction to TensorFlow [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_02%20Introduction%20to%20TensorFlow.pdf) [[video]](https://www.youtube.com/watch?v=JO0LwmIlWw0&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=2) ### Deep Learning 3: Neural Networks Foundations [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_03%20Neural%20Networks%20Foundations.pdf) [[video]](https://www.youtube.com/watch?v=5eAXoPSBgnE&index=3&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) ### Reinforcement Learning 1: Introduction to Reinforcement Learning [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_01%20Introduction%20to%20Reinforcement%20Learning.pdf) [[video]](https://www.youtube.com/watch?v=ISk80iLhdfU&index=4&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) ### Reinforcement Learning 2: Exploration and Exploitation [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_02%20Exploration%20and%20Exploitation.pdf) [[video]](https://www.youtube.com/watch?v=eM6IBYVqXEA&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=5) ### Reinforcement Learning 3: Markov Decision Processes and Dynamic Programming [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_03%20Markov%20Decision%20Processes%20and%20Dynamic%20Programming.pdf) [[video]](https://www.youtube.com/watch?v=hMbxmRyDw5M&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=6) ### Reinforcement Learning 4: Model-Free Prediction and Control [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_04%20Model-Free%20Prediction%20and%20Control.pdf) [[video]](https://www.youtube.com/watch?v=nnxHlg-2WgA&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=7) ### Deep Learning 4: Beyond Image Recognition, End-to-End Learning, Embeddings [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_04%20Beyond%20Image%20Recognition%2C%20End-to-End%20Learning%2C%20Embeddings.pdf) [[video]](https://www.youtube.com/watch?v=OfKnA91zs9I&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=8) ### Reinforcement Learning 5: Function Approximation and Deep Reinforcement Learning [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_05%20Function%20Approximation%20and%20Deep%20Reinforcement%20Learning.pdf) [[video]](https://www.youtube.com/watch?v=wAk1lxmiW4c&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=9) ### Reinforcement Learning 6: Policy Gradients and Actor Critics [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_06%20Policy%20Gradients%20and%20Actor%20Critics.pdf) [[video]](https://www.youtube.com/watch?v=bRfUxQs6xIM&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=10) ### Deep Learning 5: Optimization for Machine Learning [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_05%20Optimization%20for%20Machine%20Learning.pdf) [[video]](https://www.youtube.com/watch?v=ALdsqfrLieg&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=11) ### Reinforcement Learning 7: Planning and Models [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_07%20Planning%20and%20Models.pdf) [[video]](https://www.youtube.com/watch?v=Xrxrd8nl4YI&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=12) ### Deep Learning 6: Deep Learning for NLP [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_06%20Deep%20Learning%20for%20NLP.pdf) [[video]](https://www.youtube.com/watch?v=Y95JwaynE40&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=13) ### Reinforcement Learning 8: Advanced Topics in Deep RL [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/rl_08%20Advanced%20Topics%20in%20Deep%20RL.pdf) [[video]](https://www.youtube.com/watch?v=L6xaQ501jEs&index=14&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) ### Deep Learning 7. Attention and Memory in Deep Learning [[slides]](https://github.com/enggen/Advanced-Deep-Learning-and-Reinforcement-Learning-DeepMind/blob/master/lecture%20slides/dl_07%20Attention%20and%20Memory%20in%20Deep%20Learning.pdf) [[video]](https://www.youtube.com/watch?v=Q57rzaHHO0k&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=15) ### Reinforcement Learning 9: A Brief Tour of Deep RL Agents [[slides]]() [[video]](https://www.youtube.com/watch?v=-mhBD8Frkc4&index=16&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) ### Deep Learning 8: Unsupervised learning and generative models [[slides]](https://github.com/enggen/DeepMind-Advanced-Deep-Learning-and-Reinforcement-Learning/blob/master/lecture%20slides/dl_08%20Unsupervised%20learning%20and%20generative%20models.pdf) [[video]](https://www.youtube.com/watch?v=H4VGSYGvJiA&index=17&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs) ### Reinforcement Learning 10: Classic Games Case Study [[slides]]() [[video]](https://www.youtube.com/watch?v=ld28AU7DDB4&list=PLqYmG7hTraZDNJre23vqCGIVpfZ_K2RZs&index=18)

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