[ WebToolTip.com ] Deep Learning with Python, Third Edition, Video Edition

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[ WebToolTip.com ] Deep Learning with Python, Third Edition, Video Edition

磁力链接/BT种子简介

种子哈希：5a721563edf334b9afdeb08a4ce0c5a00d9666d0
文件大小： 2.48G
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收录时间：2025-12-08
最近下载：2025-12-08

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文件列表

  • ~Get Your Files Here !/070. Chapter 13. Recurrent neural networks.mp4 76.5 MB
  • ~Get Your Files Here !/102. Chapter 19. The missing ingredients - Search and symbols.mp4 73.8 MB
  • ~Get Your Files Here !/103. Chapter 20. Conclusions.mp4 69.9 MB
  • ~Get Your Files Here !/081. Chapter 15. The Transformer architecture.mp4 66.3 MB
  • ~Get Your Files Here !/016. Chapter 2. The engine of neural networks - Gradient-based optimization.mp4 63.2 MB
  • ~Get Your Files Here !/035. Chapter 6. The universal workflow of machine learning.mp4 63.1 MB
  • ~Get Your Files Here !/077. Chapter 14. Sequence models.mp4 60.3 MB
  • ~Get Your Files Here !/101. Chapter 19. How to build intelligence.mp4 59.0 MB
  • ~Get Your Files Here !/086. Chapter 16. Training a mini-GPT.mp4 56.3 MB
  • ~Get Your Files Here !/030. Chapter 5. Fundamentals of machine learning.mp4 54.3 MB
  • ~Get Your Files Here !/100. Chapter 19. Scale isn t all you need.mp4 52.1 MB
  • ~Get Your Files Here !/045. Chapter 8. Training a ConvNet from scratch on a small dataset.mp4 50.7 MB
  • ~Get Your Files Here !/024. Chapter 3. Introduction to Keras.mp4 50.6 MB
  • ~Get Your Files Here !/026. Chapter 4. Classification and regression.mp4 50.1 MB
  • ~Get Your Files Here !/044. Chapter 8. Image classification.mp4 50.1 MB
  • ~Get Your Files Here !/088. Chapter 16. Going further with LLMs.mp4 48.8 MB
  • ~Get Your Files Here !/095. Chapter 18. Best practices for the real world.mp4 48.7 MB
  • ~Get Your Files Here !/099. Chapter 19. The future of AI.mp4 45.4 MB
  • ~Get Your Files Here !/046. Chapter 8. Using a pretrained model.mp4 44.5 MB
  • ~Get Your Files Here !/096. Chapter 18. Scaling up model training with multiple devices.mp4 43.8 MB
  • ~Get Your Files Here !/074. Chapter 14. Preparing text data.mp4 42.8 MB
  • ~Get Your Files Here !/033. Chapter 5. Improving generalization.mp4 42.4 MB
  • ~Get Your Files Here !/065. Chapter 12. Training a YOLO model from scratch.mp4 41.6 MB
  • ~Get Your Files Here !/069. Chapter 13. A temperature forecasting example.mp4 41.2 MB
  • ~Get Your Files Here !/042. Chapter 7. Writing your own training and evaluation loops.mp4 40.4 MB
  • ~Get Your Files Here !/037. Chapter 6. Deploying your model.mp4 39.7 MB
  • ~Get Your Files Here !/091. Chapter 17. Image generation.mp4 38.9 MB
  • ~Get Your Files Here !/021. Chapter 3. Introduction to TensorFlow.mp4 37.2 MB
  • ~Get Your Files Here !/082. Chapter 15. Classification with a pretrained Transformer.mp4 35.1 MB
  • ~Get Your Files Here !/087. Chapter 16. Using a pretrained LLM.mp4 34.9 MB
  • ~Get Your Files Here !/014. Chapter 2. Data representations for neural networks.mp4 34.1 MB
  • ~Get Your Files Here !/040. Chapter 7. Different ways to build Keras models.mp4 34.1 MB
  • ~Get Your Files Here !/036. Chapter 6. Developing a model.mp4 33.3 MB
  • ~Get Your Files Here !/092. Chapter 17. Diffusion models.mp4 33.2 MB
  • ~Get Your Files Here !/097. Chapter 18. Speeding up training and inference with lower-precision computation.mp4 32.2 MB
  • ~Get Your Files Here !/015. Chapter 2. The gears of neural networks - Tensor operations.mp4 32.2 MB
  • ~Get Your Files Here !/079. Chapter 15. Language models and the Transformer.mp4 30.8 MB
  • ~Get Your Files Here !/080. Chapter 15. Sequence-to-sequence learning.mp4 30.4 MB
  • ~Get Your Files Here !/073. Chapter 14. Text classification.mp4 29.2 MB
  • ~Get Your Files Here !/023. Chapter 3. Introduction to JAX.mp4 28.8 MB
  • ~Get Your Files Here !/022. Chapter 3. Introduction to PyTorch.mp4 28.2 MB
  • ~Get Your Files Here !/031. Chapter 5. Evaluating machine-learning models.mp4 26.5 MB
  • ~Get Your Files Here !/076. Chapter 14. Set models.mp4 26.5 MB
  • ~Get Your Files Here !/083. Chapter 15. What makes the Transformer effective.mp4 26.5 MB
  • ~Get Your Files Here !/028. Chapter 4. Predicting house prices - A regression example.mp4 26.2 MB
  • ~Get Your Files Here !/085. Chapter 16. Text generation.mp4 26.1 MB
  • ~Get Your Files Here !/041. Chapter 7. Using built-in training and evaluation loops.mp4 25.8 MB
  • ~Get Your Files Here !/048. Chapter 9. ConvNet architecture patterns.mp4 25.3 MB
  • ~Get Your Files Here !/061. Chapter 11. Training a segmentation model from scratch.mp4 24.9 MB
  • ~Get Your Files Here !/027. Chapter 4. Classifying newswires - A multiclass classification example.mp4 24.8 MB
  • ~Get Your Files Here !/093. Chapter 17. Text-to-image models.mp4 24.7 MB
  • ~Get Your Files Here !/013. Chapter 2. The mathematical building blocks of neural networks.mp4 23.3 MB
  • ~Get Your Files Here !/055. Chapter 10. Interpreting what ConvNets learn.mp4 22.9 MB
  • ~Get Your Files Here !/062. Chapter 11. Using a pretrained segmentation model.mp4 21.8 MB
  • ~Get Your Files Here !/019. Chapter 3. Introduction to TensorFlow, PyTorch, JAX, and Keras.mp4 21.0 MB
  • ~Get Your Files Here !/017. Chapter 2. Looking back at our first example.mp4 20.2 MB
  • ~Get Your Files Here !/056. Chapter 10. Visualizing ConvNet filters.mp4 18.6 MB
  • ~Get Your Files Here !/051. Chapter 9. Depthwise separable convolutions.mp4 18.1 MB
  • ~Get Your Files Here !/004. Chapter 1. Learning rules and representations from data.mp4 17.8 MB
  • ~Get Your Files Here !/032. Chapter 5. Improving model fit.mp4 16.4 MB
  • ~Get Your Files Here !/057. Chapter 10. Visualizing heatmaps of class activation.mp4 16.4 MB
  • ~Get Your Files Here !/010. Chapter 1. Beware of the short-term hype.mp4 15.8 MB
  • ~Get Your Files Here !/064. Chapter 12. Object detection.mp4 15.0 MB
  • ~Get Your Files Here !/075. Chapter 14. Sets vs. sequences.mp4 14.0 MB
  • ~Get Your Files Here !/050. Chapter 9. Batch normalization.mp4 13.2 MB
  • ~Get Your Files Here !/003. Chapter 1. Machine learning.mp4 13.2 MB
  • ~Get Your Files Here !/060. Chapter 11. Image segmentation.mp4 12.8 MB
  • ~Get Your Files Here !/106. Chapter 20. Staying up to date in a fast-moving field.mp4 12.1 MB
  • ~Get Your Files Here !/066. Chapter 12. Using a pretrained RetinaNet detector.mp4 11.6 MB
  • ~Get Your Files Here !/011. Chapter 1. Summer can turn to winter.mp4 11.6 MB
  • ~Get Your Files Here !/039. Chapter 7. A deep dive on Keras.mp4 11.5 MB
  • ~Get Your Files Here !/005. Chapter 1. The deep in deep learning .mp4 10.3 MB
  • ~Get Your Files Here !/089. Chapter 16. Where are LLMs heading next.mp4 9.8 MB
  • ~Get Your Files Here !/104. Chapter 20. Limitations of deep learning.mp4 9.1 MB
  • ~Get Your Files Here !/049. Chapter 9. Residual connections.mp4 8.9 MB
  • ~Get Your Files Here !/012. Chapter 1. The promise of AI.mp4 8.9 MB
  • ~Get Your Files Here !/058. Chapter 10. Visualizing the latent space of a ConvNet.mp4 8.4 MB
  • ~Get Your Files Here !/007. Chapter 1. Understanding how deep learning works, in three figures.mp4 8.3 MB
  • ~Get Your Files Here !/068. Chapter 13. Timeseries forecasting.mp4 8.1 MB
  • ~Get Your Files Here !/002. Chapter 1. Artificial intelligence.mp4 7.9 MB
  • ~Get Your Files Here !/084. Chapter 15. Summary.mp4 7.6 MB
  • ~Get Your Files Here !/105. Chapter 20. What might lie ahead.mp4 7.3 MB
  • ~Get Your Files Here !/071. Chapter 13. Going even further.mp4 7.2 MB
  • ~Get Your Files Here !/006. Chapter 1. Understanding how deep learning works, in three figures.mp4 7.2 MB
  • ~Get Your Files Here !/034. Chapter 5. Summary.mp4 7.2 MB
  • ~Get Your Files Here !/009. Chapter 1. What deep learning has achieved so far.mp4 6.8 MB
  • ~Get Your Files Here !/053. Chapter 9. Beyond convolution - Vision Transformers.mp4 6.4 MB
  • ~Get Your Files Here !/020. Chapter 3. How these frameworks relate to each other.mp4 6.2 MB
  • ~Get Your Files Here !/052. Chapter 9. Putting it together - A mini Xception-like model.mp4 6.2 MB
  • ~Get Your Files Here !/001. Chapter 1. What is deep learning.mp4 5.2 MB
  • ~Get Your Files Here !/072. Chapter 13. Summary.mp4 5.2 MB
  • ~Get Your Files Here !/018. Chapter 2. Summary.mp4 4.7 MB
  • ~Get Your Files Here !/008. Chapter 1. The age of generative AI.mp4 4.6 MB
  • ~Get Your Files Here !/094. Chapter 17. Summary.mp4 4.2 MB
  • ~Get Your Files Here !/025. Chapter 3. Summary.mp4 4.2 MB
  • ~Get Your Files Here !/043. Chapter 7. Summary.mp4 4.2 MB
  • ~Get Your Files Here !/038. Chapter 6. Summary.mp4 4.1 MB
  • ~Get Your Files Here !/090. Chapter 16. Summary.mp4 4.1 MB
  • ~Get Your Files Here !/078. Chapter 14. Summary.mp4 3.7 MB
  • ~Get Your Files Here !/067. Chapter 12. Summary.mp4 3.4 MB
  • ~Get Your Files Here !/098. Chapter 18. Summary.mp4 3.4 MB
  • ~Get Your Files Here !/047. Chapter 8. Summary.mp4 3.0 MB
  • ~Get Your Files Here !/063. Chapter 11. Summary.mp4 2.3 MB
  • ~Get Your Files Here !/029. Chapter 4. Summary.mp4 2.2 MB
  • ~Get Your Files Here !/054. Chapter 9. Summary.mp4 1.8 MB
  • ~Get Your Files Here !/059. Chapter 10. Summary.mp4 1.7 MB
  • ~Get Your Files Here !/107. Chapter 20. Final words.mp4 1.6 MB
  • ~Get Your Files Here !/070. Chapter 13. Recurrent neural networks.en.srt 46.1 kB
  • ~Get Your Files Here !/081. Chapter 15. The Transformer architecture.en.srt 38.5 kB
  • ~Get Your Files Here !/102. Chapter 19. The missing ingredients - Search and symbols.en.srt 37.0 kB
  • ~Get Your Files Here !/077. Chapter 14. Sequence models.en.srt 36.4 kB
  • ~Get Your Files Here !/016. Chapter 2. The engine of neural networks - Gradient-based optimization.en.srt 36.0 kB
  • ~Get Your Files Here !/030. Chapter 5. Fundamentals of machine learning.en.srt 33.5 kB
  • ~Get Your Files Here !/095. Chapter 18. Best practices for the real world.en.srt 32.8 kB
  • ~Get Your Files Here !/103. Chapter 20. Conclusions.en.srt 31.8 kB
  • ~Get Your Files Here !/035. Chapter 6. The universal workflow of machine learning.en.srt 30.8 kB
  • ~Get Your Files Here !/086. Chapter 16. Training a mini-GPT.en.srt 30.6 kB
  • ~Get Your Files Here !/101. Chapter 19. How to build intelligence.en.srt 28.9 kB
  • ~Get Your Files Here !/024. Chapter 3. Introduction to Keras.en.srt 28.7 kB
  • ~Get Your Files Here !/026. Chapter 4. Classification and regression.en.srt 28.6 kB
  • ~Get Your Files Here !/088. Chapter 16. Going further with LLMs.en.srt 28.3 kB
  • ~Get Your Files Here !/045. Chapter 8. Training a ConvNet from scratch on a small dataset.en.srt 28.1 kB
  • ~Get Your Files Here !/044. Chapter 8. Image classification.en.srt 27.6 kB
  • ~Get Your Files Here !/096. Chapter 18. Scaling up model training with multiple devices.en.srt 26.0 kB
  • ~Get Your Files Here !/033. Chapter 5. Improving generalization.en.srt 25.6 kB
  • ~Get Your Files Here !/015. Chapter 2. The gears of neural networks - Tensor operations.en.srt 24.3 kB
  • ~Get Your Files Here !/042. Chapter 7. Writing your own training and evaluation loops.en.srt 24.3 kB
  • ~Get Your Files Here !/046. Chapter 8. Using a pretrained model.en.srt 24.2 kB
  • ~Get Your Files Here !/074. Chapter 14. Preparing text data.en.srt 24.2 kB
  • ~Get Your Files Here !/100. Chapter 19. Scale isn t all you need.en.srt 22.7 kB
  • ~Get Your Files Here !/099. Chapter 19. The future of AI.en.srt 22.2 kB
  • ~Get Your Files Here !/037. Chapter 6. Deploying your model.en.srt 22.1 kB
  • ~Get Your Files Here !/069. Chapter 13. A temperature forecasting example.en.srt 21.9 kB
  • ~Get Your Files Here !/021. Chapter 3. Introduction to TensorFlow.en.srt 21.7 kB
  • ~Get Your Files Here !/087. Chapter 16. Using a pretrained LLM.en.srt 21.7 kB
  • ~Get Your Files Here !/091. Chapter 17. Image generation.en.srt 20.8 kB
  • ~Get Your Files Here !/040. Chapter 7. Different ways to build Keras models.en.srt 20.7 kB
  • ~Get Your Files Here !/065. Chapter 12. Training a YOLO model from scratch.en.srt 20.2 kB
  • ~Get Your Files Here !/082. Chapter 15. Classification with a pretrained Transformer.en.srt 19.5 kB
  • ~Get Your Files Here !/036. Chapter 6. Developing a model.en.srt 19.0 kB
  • ~Get Your Files Here !/097. Chapter 18. Speeding up training and inference with lower-precision computation.en.srt 18.9 kB
  • ~Get Your Files Here !/022. Chapter 3. Introduction to PyTorch.en.srt 18.3 kB
  • ~Get Your Files Here !/014. Chapter 2. Data representations for neural networks.en.srt 18.2 kB
  • ~Get Your Files Here !/092. Chapter 17. Diffusion models.en.srt 18.0 kB
  • ~Get Your Files Here !/023. Chapter 3. Introduction to JAX.en.srt 17.9 kB
  • ~Get Your Files Here !/079. Chapter 15. Language models and the Transformer.en.srt 16.6 kB
  • ~Get Your Files Here !/028. Chapter 4. Predicting house prices - A regression example.en.srt 15.9 kB
  • ~Get Your Files Here !/041. Chapter 7. Using built-in training and evaluation loops.en.srt 15.1 kB
  • ~Get Your Files Here !/013. Chapter 2. The mathematical building blocks of neural networks.en.srt 15.0 kB
  • ~Get Your Files Here !/031. Chapter 5. Evaluating machine-learning models.en.srt 15.0 kB
  • ~Get Your Files Here !/080. Chapter 15. Sequence-to-sequence learning.en.srt 14.9 kB
  • ~Get Your Files Here !/027. Chapter 4. Classifying newswires - A multiclass classification example.en.srt 14.8 kB
  • ~Get Your Files Here !/062. Chapter 11. Using a pretrained segmentation model.en.srt 14.1 kB
  • ~Get Your Files Here !/085. Chapter 16. Text generation.en.srt 14.0 kB
  • ~Get Your Files Here !/076. Chapter 14. Set models.en.srt 14.0 kB
  • ~Get Your Files Here !/093. Chapter 17. Text-to-image models.en.srt 13.8 kB
  • ~Get Your Files Here !/073. Chapter 14. Text classification.en.srt 12.7 kB
  • ~Get Your Files Here !/083. Chapter 15. What makes the Transformer effective.en.srt 12.3 kB
  • ~Get Your Files Here !/048. Chapter 9. ConvNet architecture patterns.en.srt 11.9 kB
  • ~Get Your Files Here !/017. Chapter 2. Looking back at our first example.en.srt 11.6 kB
  • ~Get Your Files Here !/055. Chapter 10. Interpreting what ConvNets learn.en.srt 11.3 kB
  • ~Get Your Files Here !/056. Chapter 10. Visualizing ConvNet filters.en.srt 11.2 kB
  • ~Get Your Files Here !/061. Chapter 11. Training a segmentation model from scratch.en.srt 10.5 kB
  • ~Get Your Files Here !/004. Chapter 1. Learning rules and representations from data.en.srt 9.8 kB
  • ~Get Your Files Here !/032. Chapter 5. Improving model fit.en.srt 9.7 kB
  • ~Get Your Files Here !/019. Chapter 3. Introduction to TensorFlow, PyTorch, JAX, and Keras.en.srt 9.6 kB
  • ~Get Your Files Here !/057. Chapter 10. Visualizing heatmaps of class activation.en.srt 8.4 kB
  • ~Get Your Files Here !/064. Chapter 12. Object detection.en.srt 8.2 kB
  • ~Get Your Files Here !/075. Chapter 14. Sets vs. sequences.en.srt 8.0 kB
  • ~Get Your Files Here !/051. Chapter 9. Depthwise separable convolutions.en.srt 7.8 kB
  • ~Get Your Files Here !/050. Chapter 9. Batch normalization.en.srt 7.1 kB
  • ~Get Your Files Here !/010. Chapter 1. Beware of the short-term hype.en.srt 6.7 kB
  • ~Get Your Files Here !/060. Chapter 11. Image segmentation.en.srt 6.5 kB
  • ~Get Your Files Here !/003. Chapter 1. Machine learning.en.srt 6.2 kB
  • ~Get Your Files Here !/066. Chapter 12. Using a pretrained RetinaNet detector.en.srt 5.9 kB
  • ~Get Your Files Here !/039. Chapter 7. A deep dive on Keras.en.srt 5.8 kB
  • ~Get Your Files Here !/106. Chapter 20. Staying up to date in a fast-moving field.en.srt 5.8 kB
  • ~Get Your Files Here !/089. Chapter 16. Where are LLMs heading next.en.srt 5.2 kB
  • ~Get Your Files Here !/058. Chapter 10. Visualizing the latent space of a ConvNet.en.srt 4.9 kB
  • ~Get Your Files Here !/049. Chapter 9. Residual connections.en.srt 4.8 kB
  • ~Get Your Files Here !/104. Chapter 20. Limitations of deep learning.en.srt 4.7 kB
  • ~Get Your Files Here !/005. Chapter 1. The deep in deep learning .en.srt 4.6 kB
  • ~Get Your Files Here !/006. Chapter 1. Understanding how deep learning works, in three figures.en.srt 4.4 kB
  • ~Get Your Files Here !/011. Chapter 1. Summer can turn to winter.en.srt 4.4 kB
  • ~Get Your Files Here !/012. Chapter 1. The promise of AI.en.srt 4.4 kB
  • ~Get Your Files Here !/071. Chapter 13. Going even further.en.srt 4.1 kB
  • ~Get Your Files Here !/068. Chapter 13. Timeseries forecasting.en.srt 3.9 kB
  • ~Get Your Files Here !/002. Chapter 1. Artificial intelligence.en.srt 3.9 kB
  • ~Get Your Files Here !/007. Chapter 1. Understanding how deep learning works, in three figures.en.srt 3.8 kB
  • ~Get Your Files Here !/053. Chapter 9. Beyond convolution - Vision Transformers.en.srt 3.6 kB
  • ~Get Your Files Here !/105. Chapter 20. What might lie ahead.en.srt 3.4 kB
  • ~Get Your Files Here !/008. Chapter 1. The age of generative AI.en.srt 3.1 kB
  • ~Get Your Files Here !/020. Chapter 3. How these frameworks relate to each other.en.srt 3.1 kB
  • ~Get Your Files Here !/052. Chapter 9. Putting it together - A mini Xception-like model.en.srt 3.0 kB
  • ~Get Your Files Here !/034. Chapter 5. Summary.en.srt 3.0 kB
  • ~Get Your Files Here !/018. Chapter 2. Summary.en.srt 3.0 kB
  • ~Get Your Files Here !/084. Chapter 15. Summary.en.srt 2.9 kB
  • ~Get Your Files Here !/009. Chapter 1. What deep learning has achieved so far.en.srt 2.7 kB
  • ~Get Your Files Here !/090. Chapter 16. Summary.en.srt 2.5 kB
  • ~Get Your Files Here !/001. Chapter 1. What is deep learning.en.srt 2.4 kB
  • ~Get Your Files Here !/078. Chapter 14. Summary.en.srt 2.1 kB
  • ~Get Your Files Here !/094. Chapter 17. Summary.en.srt 2.0 kB
  • ~Get Your Files Here !/038. Chapter 6. Summary.en.srt 1.9 kB
  • ~Get Your Files Here !/067. Chapter 12. Summary.en.srt 1.8 kB
  • ~Get Your Files Here !/072. Chapter 13. Summary.en.srt 1.7 kB
  • ~Get Your Files Here !/029. Chapter 4. Summary.en.srt 1.4 kB
  • ~Get Your Files Here !/025. Chapter 3. Summary.en.srt 1.4 kB
  • ~Get Your Files Here !/043. Chapter 7. Summary.en.srt 1.3 kB
  • ~Get Your Files Here !/098. Chapter 18. Summary.en.srt 1.1 kB
  • ~Get Your Files Here !/047. Chapter 8. Summary.en.srt 1.1 kB
  • ~Get Your Files Here !/063. Chapter 11. Summary.en.srt 856 Bytes
  • ~Get Your Files Here !/059. Chapter 10. Summary.en.srt 789 Bytes
  • ~Get Your Files Here !/107. Chapter 20. Final words.en.srt 764 Bytes
  • ~Get Your Files Here !/054. Chapter 9. Summary.en.srt 716 Bytes
  • Get Bonus Downloads Here.url 180 Bytes
  • ~Get Your Files Here !/Bonus Resources.txt 70 Bytes

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