| 001. Part 1. Foundations.en.srt | 614.4 B | ||
| 001. Part 1. Foundations.mp4 | 1 MB | ||
| 002. Chapter 1. Toward deep learning - a machine-learning introduction.en.srt | 18 KB | ||
| 002. Chapter 1. Toward deep learning - a machine-learning introduction.mp4 | 29.5 MB | ||
| 003. Chapter 1. Machine learning by example.en.srt | 18.7 KB | ||
| 003. Chapter 1. Machine learning by example.mp4 | 28.1 MB | ||
| 004. Chapter 1. Deep learning.en.srt | 7.1 KB | ||
| 004. Chapter 1. Deep learning.mp4 | 11 MB | ||
| 005. Chapter 1. What you ll learn in this book.en.srt | 2.4 KB | ||
| 005. Chapter 1. What you ll learn in this book.mp4 | 3.5 MB | ||
| 006. Chapter 1. Summary.en.srt | 2.3 KB | ||
| 006. Chapter 1. Summary.mp4 | 5.9 MB | ||
| 007. Chapter 2. Go as a machine-learning problem.en.srt | 4.2 KB | ||
| 007. Chapter 2. Go as a machine-learning problem.mp4 | 8.6 MB | ||
| 008. Chapter 2. A lightning introduction to the game of Go.en.srt | 12.7 KB | ||
| 008. Chapter 2. A lightning introduction to the game of Go.mp4 | 23 MB | ||
| 009. Chapter 2. Handicaps.en.srt | 1.2 KB | ||
| 009. Chapter 2. Handicaps.mp4 | 2.3 MB | ||
| 010. Chapter 2. Where to learn more.en.srt | 1.5 KB | ||
| 010. Chapter 2. Where to learn more.mp4 | 2.9 MB | ||
| 011. Chapter 2. What can we teach a machine.en.srt | 9.7 KB | ||
| 011. Chapter 2. What can we teach a machine.mp4 | 17.5 MB | ||
| 012. Chapter 2. How to measure your Go AI s strength.en.srt | 3.7 KB | ||
| 012. Chapter 2. How to measure your Go AI s strength.mp4 | 6.9 MB | ||
| 013. Chapter 2. Summary.en.srt | 1.3 KB | ||
| 013. Chapter 2. Summary.mp4 | 3.8 MB | ||
| 014. Chapter 3. Implementing your first Go bot.en.srt | 19.9 KB | ||
| 014. Chapter 3. Implementing your first Go bot.mp4 | 29 MB | ||
| 015. Chapter 3. Capturing game state and checking for illegal moves.en.srt | 9.2 KB | ||
| 015. Chapter 3. Capturing game state and checking for illegal moves.mp4 | 14.4 MB | ||
| 016. Chapter 3. Ending a game.en.srt | 6.4 KB | ||
| 016. Chapter 3. Ending a game.mp4 | 10.6 MB | ||
| 017. Chapter 3. Creating your first bot - the weakest Go AI imaginable.en.srt | 4.9 KB | ||
| 017. Chapter 3. Creating your first bot - the weakest Go AI imaginable.mp4 | 9.6 MB | ||
| 018. Chapter 3. Speeding up game play with Zobrist hashing.en.srt | 9.5 KB | ||
| 018. Chapter 3. Speeding up game play with Zobrist hashing.mp4 | 20 MB | ||
| 019. Chapter 3. Playing against your bot.en.srt | 2.2 KB | ||
| 019. Chapter 3. Playing against your bot.mp4 | 3.7 MB | ||
| 020. Chapter 3. Summary.en.srt | 1.6 KB | ||
| 020. Chapter 3. Summary.mp4 | 3.9 MB | ||
| 021. Part 2. Machine learning and game AI.en.srt | 1 KB | ||
| 021. Part 2. Machine learning and game AI.mp4 | 1.9 MB | ||
| 022. Chapter 4. Playing games with tree search.en.srt | 8.5 KB | ||
| 022. Chapter 4. Playing games with tree search.mp4 | 17.1 MB | ||
| 023. Chapter 4. Anticipating your opponent with minimax search.en.srt | 6.9 KB | ||
| 023. Chapter 4. Anticipating your opponent with minimax search.mp4 | 10.2 MB | ||
| 024. Chapter 4. Solving tic-tac-toe - a minimax example.en.srt | 4.8 KB | ||
| 024. Chapter 4. Solving tic-tac-toe - a minimax example.mp4 | 9.5 MB | ||
| 025. Chapter 4. Reducing search space with pruning.en.srt | 21 KB | ||
| 025. Chapter 4. Reducing search space with pruning.mp4 | 35 MB | ||
| 026. Chapter 4. Evaluating game states with Monte Carlo tree search.en.srt | 24.9 KB | ||
| 026. Chapter 4. Evaluating game states with Monte Carlo tree search.mp4 | 44.2 MB | ||
| 027. Chapter 4. Summary.en.srt | 1.9 KB | ||
| 027. Chapter 4. Summary.mp4 | 5.9 MB | ||
| 028. Chapter 5. Getting started with neural networks.en.srt | 25.2 KB | ||
| 028. Chapter 5. Getting started with neural networks.mp4 | 45.7 MB | ||
| 029. Chapter 5. The basics of neural networks.en.srt | 4.6 KB | ||
| 029. Chapter 5. The basics of neural networks.mp4 | 6.9 MB | ||
| 030. Chapter 5. Feed-forward networks.en.srt | 8.9 KB | ||
| 030. Chapter 5. Feed-forward networks.mp4 | 20.3 MB | ||
| 031. Chapter 5. How good are our predictions Loss functions and optimization.en.srt | 21 KB | ||
| 031. Chapter 5. How good are our predictions Loss functions and optimization.mp4 | 38.6 MB | ||
| 032. Chapter 5. Training a neural network step-by-step in Python.en.srt | 16.2 KB | ||
| 032. Chapter 5. Training a neural network step-by-step in Python.mp4 | 30 MB | ||
| 033. Chapter 5. Summary.en.srt | 2.5 KB | ||
| 033. Chapter 5. Summary.mp4 | 5.8 MB | ||
| 034. Chapter 6. Designing a neural network for Go data.en.srt | 10.4 KB | ||
| 034. Chapter 6. Designing a neural network for Go data.mp4 | 22.1 MB | ||
| 035. Chapter 6. Generating tree-search games as network training data.en.srt | 5.5 KB | ||
| 035. Chapter 6. Generating tree-search games as network training data.mp4 | 11.5 MB | ||
| 036. Chapter 6. Using the Keras deep-learning library.en.srt | 20.2 KB | ||
| 036. Chapter 6. Using the Keras deep-learning library.mp4 | 34.4 MB | ||
| 037. Chapter 6. Analyzing space with convolutional networks.en.srt | 17.2 KB | ||
| 037. Chapter 6. Analyzing space with convolutional networks.mp4 | 34.5 MB | ||
| 038. Chapter 6. Predicting Go move probabilities.en.srt | 11.1 KB | ||
| 038. Chapter 6. Predicting Go move probabilities.mp4 | 23.5 MB | ||
| 039. Chapter 6. Building deeper networks with dropout and rectified linear units.en.srt | 5.9 KB | ||
| 039. Chapter 6. Building deeper networks with dropout and rectified linear units.mp4 | 11.6 MB | ||
| 040. Chapter 6. Putting it all together for a stronger Go move-prediction network.en.srt | 6.2 KB | ||
| 040. Chapter 6. Putting it all together for a stronger Go move-prediction network.mp4 | 12.5 MB | ||
| 041. Chapter 6. Summary.en.srt | 1.5 KB | ||
| 041. Chapter 6. Summary.mp4 | 4.6 MB | ||
| 042. Chapter 7. Learning from data - a deep-learning bot.en.srt | 12.1 KB | ||
| 042. Chapter 7. Learning from data - a deep-learning bot.mp4 | 23.6 MB | ||
| 043. Chapter 7. Preparing Go data for deep learning.en.srt | 22.9 KB | ||
| 043. Chapter 7. Preparing Go data for deep learning.mp4 | 43 MB | ||
| 044. Chapter 7. Training a deep-learning model on human game-play data.en.srt | 12.1 KB | ||
| 044. Chapter 7. Training a deep-learning model on human game-play data.mp4 | 25.9 MB | ||
| 045. Chapter 7. Building more-realistic Go data encoders.en.srt | 5.6 KB | ||
| 045. Chapter 7. Building more-realistic Go data encoders.mp4 | 11.5 MB | ||
| 046. Chapter 7. Training efficiently with adaptive gradients.en.srt | 11.6 KB | ||
| 046. Chapter 7. Training efficiently with adaptive gradients.mp4 | 20.6 MB | ||
| 047. Chapter 7. Running your own experiments and evaluating performance.en.srt | 14.3 KB | ||
| 047. Chapter 7. Running your own experiments and evaluating performance.mp4 | 35.9 MB | ||
| 048. Chapter 7. Summary.en.srt | 1.5 KB | ||
| 048. Chapter 7. Summary.mp4 | 4.3 MB | ||
| 049. Chapter 8. Deploying bots in the wild.en.srt | 10.2 KB | ||
| 049. Chapter 8. Deploying bots in the wild.mp4 | 22 MB | ||
| 050. Chapter 8. Serving your Go bot to a web frontend.en.srt | 6.6 KB | ||
| 050. Chapter 8. Serving your Go bot to a web frontend.mp4 | 12 MB | ||
| 051. Chapter 8. Training and deploying a Go bot in the cloud.en.srt | 2.7 KB | ||
| 051. Chapter 8. Training and deploying a Go bot in the cloud.mp4 | 5.3 MB | ||
| 052. Chapter 8. Talking to other bots - the Go Text Protocol.en.srt | 6.6 KB | ||
| 052. Chapter 8. Talking to other bots - the Go Text Protocol.mp4 | 14.2 MB | ||
| 053. Chapter 8. Competing against other bots locally.en.srt | 11 KB | ||
| 053. Chapter 8. Competing against other bots locally.mp4 | 17.7 MB | ||
| 054. Chapter 8. Deploying a Go bot to an online Go server.en.srt | 6.2 KB | ||
| 054. Chapter 8. Deploying a Go bot to an online Go server.mp4 | 12 MB | ||
| 055. Chapter 8. Summary.en.srt | 1.2 KB | ||
| 055. Chapter 8. Summary.mp4 | 3.8 MB | ||
| 056. Chapter 9. Learning by practice - reinforcement learning.en.srt | 8.6 KB | ||
| 056. Chapter 9. Learning by practice - reinforcement learning.mp4 | 15.5 MB | ||
| 057. Chapter 9. What goes into experience.en.srt | 8.7 KB | ||
| 057. Chapter 9. What goes into experience.mp4 | 14.3 MB | ||
| 058. Chapter 9. Building an agent that can learn.en.srt | 15.1 KB | ||
| 058. Chapter 9. Building an agent that can learn.mp4 | 26.8 MB | ||
| 059. Chapter 9. Self-play - how a computer program practices.en.srt | 9.7 KB | ||
| 059. Chapter 9. Self-play - how a computer program practices.mp4 | 18.6 MB | ||
| 060. Chapter 9. Summary.en.srt | 1.9 KB | ||
| 060. Chapter 9. Summary.mp4 | 5.5 MB | ||
| 061. Chapter 10. Reinforcement learning with policy gradients.en.srt | 11 KB | ||
| 061. Chapter 10. Reinforcement learning with policy gradients.mp4 | 19 MB | ||
| 062. Chapter 10. Modifying neural network policies with gradient descent.en.srt | 12.2 KB | ||
| 062. Chapter 10. Modifying neural network policies with gradient descent.mp4 | 21.8 MB | ||
| 063. Chapter 10. Tips for training with self-play.en.srt | 16.5 KB | ||
| 063. Chapter 10. Tips for training with self-play.mp4 | 27.8 MB | ||
| 064. Chapter 10. Summary.en.srt | 1.8 KB | ||
| 064. Chapter 10. Summary.mp4 | 5.1 MB | ||
| 065. Chapter 11. Reinforcement learning with value methods.en.srt | 12.4 KB | ||
| 065. Chapter 11. Reinforcement learning with value methods.mp4 | 20.2 MB | ||
| 066. Chapter 11. Q-learning with Keras.en.srt | 13.8 KB | ||
| 066. Chapter 11. Q-learning with Keras.mp4 | 24.1 MB | ||
| 067. Chapter 11. Summary.en.srt | 1.2 KB | ||
| 067. Chapter 11. Summary.mp4 | 3.7 MB | ||
| 068. Chapter 12. Reinforcement learning with actor-critic methods.en.srt | 14.3 KB | ||
| 068. Chapter 12. Reinforcement learning with actor-critic methods.mp4 | 25.2 MB | ||
| 069. Chapter 12. Designing a neural network for actor-critic learning.en.srt | 3.9 KB | ||
| 069. Chapter 12. Designing a neural network for actor-critic learning.mp4 | 8.1 MB | ||
| 070. Chapter 12. Playing games with an actor-critic agent.en.srt | 1 KB | ||
| 070. Chapter 12. Playing games with an actor-critic agent.mp4 | 2.1 MB | ||
| 071. Chapter 12. Training an actor-critic agent from experience data.en.srt | 11.2 KB | ||
| 071. Chapter 12. Training an actor-critic agent from experience data.mp4 | 19.4 MB | ||
| 072. Chapter 12. Summary.en.srt | 2 KB | ||
| 072. Chapter 12. Summary.mp4 | 3.6 MB | ||
| 073. Part 3. Greater than the sum of its parts.en.srt | 1 KB | ||
| 073. Part 3. Greater than the sum of its parts.mp4 | 2.1 MB | ||
| 074. Chapter 13. AlphaGo - Bringing it all together.en.srt | 26.5 KB | ||
| 074. Chapter 13. AlphaGo - Bringing it all together.mp4 | 51.5 MB | ||
| 075. Chapter 13. Bootstrapping self-play from policy networks.en.srt | 3.9 KB | ||
| 075. Chapter 13. Bootstrapping self-play from policy networks.mp4 | 8.1 MB | ||
| 076. Chapter 13. Deriving a value network from self-play data.en.srt | 1.8 KB | ||
| 076. Chapter 13. Deriving a value network from self-play data.mp4 | 3.5 MB | ||
| 077. Chapter 13. Better search with policy and value networks.en.srt | 25.1 KB | ||
| 077. Chapter 13. Better search with policy and value networks.mp4 | 47.7 MB | ||
| 078. Chapter 13. Practical considerations for training your own AlphaGo.en.srt | 5.4 KB | ||
| 078. Chapter 13. Practical considerations for training your own AlphaGo.mp4 | 13.8 MB | ||
| 079. Chapter 13. Summary.en.srt | 1.7 KB | ||
| 079. Chapter 13. Summary.mp4 | 5.6 MB | ||
| 080. Chapter 14. AlphaGo Zero - Integrating tree search with reinforcement learning.en.srt | 9.8 KB | ||
| 080. Chapter 14. AlphaGo Zero - Integrating tree search with reinforcement learning.mp4 | 19 MB | ||
| 081. Chapter 14. Guiding tree search with a neural network.en.srt | 21.3 KB | ||
| 081. Chapter 14. Guiding tree search with a neural network.mp4 | 28.8 MB | ||
| 082. Chapter 14. Training.en.srt | 6.7 KB | ||
| 082. Chapter 14. Training.mp4 | 12.9 MB | ||
| 083. Chapter 14. Improving exploration with Dirichlet noise.en.srt | 4.7 KB | ||
| 083. Chapter 14. Improving exploration with Dirichlet noise.mp4 | 9.5 MB | ||
| 084. Chapter 14. Modern techniques for deeper neural networks.en.srt | 6.5 KB | ||
| 084. Chapter 14. Modern techniques for deeper neural networks.mp4 | 11.4 MB | ||
| 085. Chapter 14. Exploring additional resources.en.srt | 2.2 KB | ||
| 085. Chapter 14. Exploring additional resources.mp4 | 5.3 MB | ||
| 086. Chapter 14. Wrapping up.en.srt | 1.2 KB | ||
| 086. Chapter 14. Wrapping up.mp4 | 1.8 MB | ||
| 087. Chapter 14. Summary.en.srt | 1.7 KB | ||
| 087. Chapter 14. Summary.mp4 | 4.7 MB | ||
| 088. Appendix A. Mathematical foundations.en.srt | 16.6 KB | ||
| 088. Appendix A. Mathematical foundations.mp4 | 24.7 MB | ||
| 089. Appendix B. The backpropagation algorithm.en.srt | 12.8 KB | ||
| 089. Appendix B. The backpropagation algorithm.mp4 | 21.2 MB | ||
| 090. Appendix C. Go programs and servers.en.srt | 7 KB | ||
| 090. Appendix C. Go programs and servers.mp4 | 16.2 MB | ||
| 091. Appendix D. Training and deploying bots by using Amazon Web Services.en.srt | 18.9 KB | ||
| 091. Appendix D. Training and deploying bots by using Amazon Web Services.mp4 | 33.8 MB | ||
| 092. Appendix E. Submitting a bot to the Online Go Server.en.srt | 17.9 KB | ||
| 092. Appendix E. Submitting a bot to the Online Go Server.mp4 | 32 MB | ||
| Bonus Resources.txt | 102.4 B | ||
| Get Bonus Downloads Here.url | 204.8 B | ||
| ▲ 186 total files | |||
Deep Learning and the Game of Go, Video Edition
https://WebToolTip.com
Last updated 01/2019
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 9h 43m | Size: 1.5 GB
Overview
In Video Editions the narrator reads the book while the content, figures, code listings, diagrams, and text appear on the screen. Like an audiobook that you can also watch as a video.
Deep Learning and the Game of Go teaches you how to apply the power of deep learning to complex reasoning tasks by building a Go-playing AI. After exposing you to the foundations of machine and deep learning, you'll use Python to build a bot and then teach it the rules of the game.
About the Technology
The ancient strategy game of Go is an incredible case study for AI. In 2016, a deep learning–based system shocked the Go world by defeating a world champion. Shortly after that, the upgraded AlphaGo Zero crushed the original bot by using deep reinforcement learning to master the game. Now, you can learn those same deep learning techniques by building your own Go bot!
About the Book
Deep Learning and the Game of Go introduces deep learning by teaching you to build a Go-winning bot. As you progress, you’ll apply increasingly complex training techniques and strategies using the Python deep learning library Keras. You’ll enjoy watching your bot master the game of Go, and along the way, you’ll discover how to apply your new deep learning skills to a wide range of other scenarios!
What's Inside
Build and teach a self-improving game AI
Enhance classical game AI systems with deep learning
Implement neural networks for deep learning
Screenshot
| torrent name | size | uploader | age | seed | leech |
|---|---|---|---|---|---|
| 4 GB | freecoursewb | 2 months | 12 | 10 | |
| 498 MB | freecoursewb | 2 months | 16 | 2 | |
| 4 GB | freecoursewb | 4 months | 24 | 10 | |
| 2.5 GB | freecoursewb | 7 months | 14 | 3 | |
| 785.3 MB | freecoursewb | 7 months | 13 | 1 |
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