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

Creation Time	Nov. 22, 2025, 4:11 p.m.
Last Access Time	Nov. 29, 2025, 9:36 a.m.
File Size	2.5 GB
Keywords	WebToolTip Third Python com Deep Edition Video Learning with
Total Requests	23
Total Files	216
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

~Get Your Files Here !/070. Chapter 13. Recurrent neural networks.mp4 72.9 MB
~Get Your Files Here !/102. Chapter 19. The missing ingredients - Search and symbols.mp4 70.4 MB
~Get Your Files Here !/103. Chapter 20. Conclusions.mp4 66.7 MB
~Get Your Files Here !/081. Chapter 15. The Transformer architecture.mp4 63.3 MB
~Get Your Files Here !/016. Chapter 2. The engine of neural networks - Gradient-based optimization.mp4 60.2 MB
~Get Your Files Here !/035. Chapter 6. The universal workflow of machine learning.mp4 60.2 MB
~Get Your Files Here !/077. Chapter 14. Sequence models.mp4 57.5 MB
~Get Your Files Here !/101. Chapter 19. How to build intelligence.mp4 56.3 MB
~Get Your Files Here !/086. Chapter 16. Training a mini-GPT.mp4 53.7 MB
~Get Your Files Here !/030. Chapter 5. Fundamentals of machine learning.mp4 51.8 MB
~Get Your Files Here !/100. Chapter 19. Scale isn t all you need.mp4 49.7 MB
~Get Your Files Here !/045. Chapter 8. Training a ConvNet from scratch on a small dataset.mp4 48.3 MB
~Get Your Files Here !/024. Chapter 3. Introduction to Keras.mp4 48.3 MB
~Get Your Files Here !/026. Chapter 4. Classification and regression.mp4 47.8 MB
~Get Your Files Here !/044. Chapter 8. Image classification.mp4 47.7 MB
~Get Your Files Here !/088. Chapter 16. Going further with LLMs.mp4 46.6 MB
~Get Your Files Here !/095. Chapter 18. Best practices for the real world.mp4 46.4 MB
~Get Your Files Here !/099. Chapter 19. The future of AI.mp4 43.3 MB
~Get Your Files Here !/046. Chapter 8. Using a pretrained model.mp4 42.4 MB
~Get Your Files Here !/096. Chapter 18. Scaling up model training with multiple devices.mp4 41.8 MB
~Get Your Files Here !/074. Chapter 14. Preparing text data.mp4 40.9 MB
~Get Your Files Here !/033. Chapter 5. Improving generalization.mp4 40.4 MB
~Get Your Files Here !/065. Chapter 12. Training a YOLO model from scratch.mp4 39.7 MB
~Get Your Files Here !/069. Chapter 13. A temperature forecasting example.mp4 39.3 MB
~Get Your Files Here !/042. Chapter 7. Writing your own training and evaluation loops.mp4 38.6 MB
~Get Your Files Here !/037. Chapter 6. Deploying your model.mp4 37.9 MB
~Get Your Files Here !/091. Chapter 17. Image generation.mp4 37.1 MB
~Get Your Files Here !/021. Chapter 3. Introduction to TensorFlow.mp4 35.5 MB
~Get Your Files Here !/082. Chapter 15. Classification with a pretrained Transformer.mp4 33.5 MB
~Get Your Files Here !/087. Chapter 16. Using a pretrained LLM.mp4 33.3 MB
~Get Your Files Here !/014. Chapter 2. Data representations for neural networks.mp4 32.6 MB
~Get Your Files Here !/040. Chapter 7. Different ways to build Keras models.mp4 32.5 MB
~Get Your Files Here !/036. Chapter 6. Developing a model.mp4 31.7 MB
~Get Your Files Here !/092. Chapter 17. Diffusion models.mp4 31.6 MB
~Get Your Files Here !/097. Chapter 18. Speeding up training and inference with lower-precision computation.mp4 30.7 MB
~Get Your Files Here !/015. Chapter 2. The gears of neural networks - Tensor operations.mp4 30.7 MB
~Get Your Files Here !/079. Chapter 15. Language models and the Transformer.mp4 29.4 MB
~Get Your Files Here !/080. Chapter 15. Sequence-to-sequence learning.mp4 29.0 MB
~Get Your Files Here !/073. Chapter 14. Text classification.mp4 27.9 MB
~Get Your Files Here !/023. Chapter 3. Introduction to JAX.mp4 27.5 MB
~Get Your Files Here !/022. Chapter 3. Introduction to PyTorch.mp4 26.9 MB
~Get Your Files Here !/031. Chapter 5. Evaluating machine-learning models.mp4 25.3 MB
~Get Your Files Here !/076. Chapter 14. Set models.mp4 25.2 MB
~Get Your Files Here !/083. Chapter 15. What makes the Transformer effective.mp4 25.2 MB
~Get Your Files Here !/028. Chapter 4. Predicting house prices - A regression example.mp4 25.0 MB
~Get Your Files Here !/085. Chapter 16. Text generation.mp4 24.9 MB
~Get Your Files Here !/041. Chapter 7. Using built-in training and evaluation loops.mp4 24.6 MB
~Get Your Files Here !/048. Chapter 9. ConvNet architecture patterns.mp4 24.1 MB
~Get Your Files Here !/061. Chapter 11. Training a segmentation model from scratch.mp4 23.8 MB
~Get Your Files Here !/027. Chapter 4. Classifying newswires - A multiclass classification example.mp4 23.6 MB
~Get Your Files Here !/093. Chapter 17. Text-to-image models.mp4 23.6 MB
~Get Your Files Here !/013. Chapter 2. The mathematical building blocks of neural networks.mp4 22.2 MB
~Get Your Files Here !/055. Chapter 10. Interpreting what ConvNets learn.mp4 21.8 MB
~Get Your Files Here !/062. Chapter 11. Using a pretrained segmentation model.mp4 20.8 MB
~Get Your Files Here !/019. Chapter 3. Introduction to TensorFlow, PyTorch, JAX, and Keras.mp4 20.0 MB
~Get Your Files Here !/017. Chapter 2. Looking back at our first example.mp4 19.3 MB
~Get Your Files Here !/056. Chapter 10. Visualizing ConvNet filters.mp4 17.7 MB
~Get Your Files Here !/051. Chapter 9. Depthwise separable convolutions.mp4 17.3 MB
~Get Your Files Here !/004. Chapter 1. Learning rules and representations from data.mp4 17.0 MB
~Get Your Files Here !/032. Chapter 5. Improving model fit.mp4 15.7 MB
~Get Your Files Here !/057. Chapter 10. Visualizing heatmaps of class activation.mp4 15.6 MB
~Get Your Files Here !/010. Chapter 1. Beware of the short-term hype.mp4 15.1 MB
~Get Your Files Here !/064. Chapter 12. Object detection.mp4 14.3 MB
~Get Your Files Here !/075. Chapter 14. Sets vs. sequences.mp4 13.3 MB
~Get Your Files Here !/050. Chapter 9. Batch normalization.mp4 12.6 MB
~Get Your Files Here !/003. Chapter 1. Machine learning.mp4 12.6 MB
~Get Your Files Here !/060. Chapter 11. Image segmentation.mp4 12.2 MB
~Get Your Files Here !/106. Chapter 20. Staying up to date in a fast-moving field.mp4 11.5 MB
~Get Your Files Here !/066. Chapter 12. Using a pretrained RetinaNet detector.mp4 11.0 MB
~Get Your Files Here !/011. Chapter 1. Summer can turn to winter.mp4 11.0 MB
~Get Your Files Here !/039. Chapter 7. A deep dive on Keras.mp4 11.0 MB
~Get Your Files Here !/005. Chapter 1. The deep in deep learning .mp4 9.8 MB
~Get Your Files Here !/089. Chapter 16. Where are LLMs heading next.mp4 9.3 MB
~Get Your Files Here !/104. Chapter 20. Limitations of deep learning.mp4 8.6 MB
~Get Your Files Here !/049. Chapter 9. Residual connections.mp4 8.5 MB
~Get Your Files Here !/012. Chapter 1. The promise of AI.mp4 8.5 MB
~Get Your Files Here !/058. Chapter 10. Visualizing the latent space of a ConvNet.mp4 8.0 MB
~Get Your Files Here !/007. Chapter 1. Understanding how deep learning works, in three figures.mp4 7.9 MB
~Get Your Files Here !/068. Chapter 13. Timeseries forecasting.mp4 7.7 MB
~Get Your Files Here !/002. Chapter 1. Artificial intelligence.mp4 7.5 MB
~Get Your Files Here !/084. Chapter 15. Summary.mp4 7.2 MB
~Get Your Files Here !/105. Chapter 20. What might lie ahead.mp4 7.0 MB
~Get Your Files Here !/071. Chapter 13. Going even further.mp4 6.9 MB
~Get Your Files Here !/006. Chapter 1. Understanding how deep learning works, in three figures.mp4 6.9 MB
~Get Your Files Here !/034. Chapter 5. Summary.mp4 6.9 MB
~Get Your Files Here !/009. Chapter 1. What deep learning has achieved so far.mp4 6.5 MB
~Get Your Files Here !/053. Chapter 9. Beyond convolution - Vision Transformers.mp4 6.1 MB
~Get Your Files Here !/020. Chapter 3. How these frameworks relate to each other.mp4 5.9 MB
~Get Your Files Here !/052. Chapter 9. Putting it together - A mini Xception-like model.mp4 5.9 MB
~Get Your Files Here !/001. Chapter 1. What is deep learning.mp4 5.0 MB
~Get Your Files Here !/072. Chapter 13. Summary.mp4 4.9 MB
~Get Your Files Here !/018. Chapter 2. Summary.mp4 4.5 MB
~Get Your Files Here !/008. Chapter 1. The age of generative AI.mp4 4.4 MB
~Get Your Files Here !/094. Chapter 17. Summary.mp4 4.0 MB
~Get Your Files Here !/025. Chapter 3. Summary.mp4 4.0 MB
~Get Your Files Here !/043. Chapter 7. Summary.mp4 4.0 MB
~Get Your Files Here !/038. Chapter 6. Summary.mp4 3.9 MB
~Get Your Files Here !/090. Chapter 16. Summary.mp4 3.9 MB
~Get Your Files Here !/078. Chapter 14. Summary.mp4 3.6 MB
~Get Your Files Here !/067. Chapter 12. Summary.mp4 3.3 MB
~Get Your Files Here !/098. Chapter 18. Summary.mp4 3.2 MB
~Get Your Files Here !/047. Chapter 8. Summary.mp4 2.9 MB
~Get Your Files Here !/063. Chapter 11. Summary.mp4 2.2 MB
~Get Your Files Here !/029. Chapter 4. Summary.mp4 2.1 MB
~Get Your Files Here !/054. Chapter 9. Summary.mp4 1.7 MB
~Get Your Files Here !/059. Chapter 10. Summary.mp4 1.6 MB
~Get Your Files Here !/107. Chapter 20. Final words.mp4 1.5 MB
~Get Your Files Here !/070. Chapter 13. Recurrent neural networks.en.srt 45.0 KB
~Get Your Files Here !/081. Chapter 15. The Transformer architecture.en.srt 37.6 KB
~Get Your Files Here !/102. Chapter 19. The missing ingredients - Search and symbols.en.srt 36.1 KB
~Get Your Files Here !/077. Chapter 14. Sequence models.en.srt 35.6 KB
~Get Your Files Here !/016. Chapter 2. The engine of neural networks - Gradient-based optimization.en.srt 35.2 KB
~Get Your Files Here !/030. Chapter 5. Fundamentals of machine learning.en.srt 32.7 KB
~Get Your Files Here !/095. Chapter 18. Best practices for the real world.en.srt 32.0 KB
~Get Your Files Here !/103. Chapter 20. Conclusions.en.srt 31.0 KB
~Get Your Files Here !/035. Chapter 6. The universal workflow of machine learning.en.srt 30.1 KB
~Get Your Files Here !/086. Chapter 16. Training a mini-GPT.en.srt 29.9 KB
~Get Your Files Here !/101. Chapter 19. How to build intelligence.en.srt 28.2 KB
~Get Your Files Here !/024. Chapter 3. Introduction to Keras.en.srt 28.1 KB
~Get Your Files Here !/026. Chapter 4. Classification and regression.en.srt 28.0 KB
~Get Your Files Here !/088. Chapter 16. Going further with LLMs.en.srt 27.6 KB
~Get Your Files Here !/045. Chapter 8. Training a ConvNet from scratch on a small dataset.en.srt 27.4 KB
~Get Your Files Here !/044. Chapter 8. Image classification.en.srt 27.0 KB
~Get Your Files Here !/096. Chapter 18. Scaling up model training with multiple devices.en.srt 25.4 KB
~Get Your Files Here !/033. Chapter 5. Improving generalization.en.srt 25.0 KB
~Get Your Files Here !/015. Chapter 2. The gears of neural networks - Tensor operations.en.srt 23.8 KB
~Get Your Files Here !/042. Chapter 7. Writing your own training and evaluation loops.en.srt 23.7 KB
~Get Your Files Here !/046. Chapter 8. Using a pretrained model.en.srt 23.6 KB
~Get Your Files Here !/074. Chapter 14. Preparing text data.en.srt 23.6 KB
~Get Your Files Here !/100. Chapter 19. Scale isn t all you need.en.srt 22.2 KB
~Get Your Files Here !/099. Chapter 19. The future of AI.en.srt 21.7 KB
~Get Your Files Here !/037. Chapter 6. Deploying your model.en.srt 21.6 KB
~Get Your Files Here !/069. Chapter 13. A temperature forecasting example.en.srt 21.4 KB
~Get Your Files Here !/021. Chapter 3. Introduction to TensorFlow.en.srt 21.2 KB
~Get Your Files Here !/087. Chapter 16. Using a pretrained LLM.en.srt 21.2 KB
~Get Your Files Here !/091. Chapter 17. Image generation.en.srt 20.3 KB
~Get Your Files Here !/040. Chapter 7. Different ways to build Keras models.en.srt 20.2 KB
~Get Your Files Here !/065. Chapter 12. Training a YOLO model from scratch.en.srt 19.7 KB
~Get Your Files Here !/082. Chapter 15. Classification with a pretrained Transformer.en.srt 19.0 KB
~Get Your Files Here !/036. Chapter 6. Developing a model.en.srt 18.5 KB
~Get Your Files Here !/097. Chapter 18. Speeding up training and inference with lower-precision computation.en.srt 18.5 KB
~Get Your Files Here !/022. Chapter 3. Introduction to PyTorch.en.srt 17.9 KB
~Get Your Files Here !/014. Chapter 2. Data representations for neural networks.en.srt 17.7 KB
~Get Your Files Here !/092. Chapter 17. Diffusion models.en.srt 17.5 KB
~Get Your Files Here !/023. Chapter 3. Introduction to JAX.en.srt 17.5 KB
~Get Your Files Here !/079. Chapter 15. Language models and the Transformer.en.srt 16.2 KB
~Get Your Files Here !/028. Chapter 4. Predicting house prices - A regression example.en.srt 15.5 KB
~Get Your Files Here !/041. Chapter 7. Using built-in training and evaluation loops.en.srt 14.7 KB
~Get Your Files Here !/013. Chapter 2. The mathematical building blocks of neural networks.en.srt 14.7 KB
~Get Your Files Here !/031. Chapter 5. Evaluating machine-learning models.en.srt 14.6 KB
~Get Your Files Here !/080. Chapter 15. Sequence-to-sequence learning.en.srt 14.5 KB
~Get Your Files Here !/027. Chapter 4. Classifying newswires - A multiclass classification example.en.srt 14.4 KB
~Get Your Files Here !/062. Chapter 11. Using a pretrained segmentation model.en.srt 13.8 KB
~Get Your Files Here !/085. Chapter 16. Text generation.en.srt 13.7 KB
~Get Your Files Here !/076. Chapter 14. Set models.en.srt 13.6 KB
~Get Your Files Here !/093. Chapter 17. Text-to-image models.en.srt 13.5 KB
~Get Your Files Here !/073. Chapter 14. Text classification.en.srt 12.4 KB
~Get Your Files Here !/083. Chapter 15. What makes the Transformer effective.en.srt 12.1 KB
~Get Your Files Here !/048. Chapter 9. ConvNet architecture patterns.en.srt 11.6 KB
~Get Your Files Here !/017. Chapter 2. Looking back at our first example.en.srt 11.4 KB
~Get Your Files Here !/055. Chapter 10. Interpreting what ConvNets learn.en.srt 11.0 KB
~Get Your Files Here !/056. Chapter 10. Visualizing ConvNet filters.en.srt 10.9 KB
~Get Your Files Here !/061. Chapter 11. Training a segmentation model from scratch.en.srt 10.3 KB
~Get Your Files Here !/004. Chapter 1. Learning rules and representations from data.en.srt 9.6 KB
~Get Your Files Here !/032. Chapter 5. Improving model fit.en.srt 9.5 KB
~Get Your Files Here !/019. Chapter 3. Introduction to TensorFlow, PyTorch, JAX, and Keras.en.srt 9.4 KB
~Get Your Files Here !/057. Chapter 10. Visualizing heatmaps of class activation.en.srt 8.2 KB
~Get Your Files Here !/064. Chapter 12. Object detection.en.srt 8.0 KB
~Get Your Files Here !/075. Chapter 14. Sets vs. sequences.en.srt 7.8 KB
~Get Your Files Here !/051. Chapter 9. Depthwise separable convolutions.en.srt 7.6 KB
~Get Your Files Here !/050. Chapter 9. Batch normalization.en.srt 7.0 KB
~Get Your Files Here !/010. Chapter 1. Beware of the short-term hype.en.srt 6.6 KB
~Get Your Files Here !/060. Chapter 11. Image segmentation.en.srt 6.4 KB
~Get Your Files Here !/003. Chapter 1. Machine learning.en.srt 6.1 KB
~Get Your Files Here !/066. Chapter 12. Using a pretrained RetinaNet detector.en.srt 5.8 KB
~Get Your Files Here !/039. Chapter 7. A deep dive on Keras.en.srt 5.6 KB
~Get Your Files Here !/106. Chapter 20. Staying up to date in a fast-moving field.en.srt 5.6 KB
~Get Your Files Here !/089. Chapter 16. Where are LLMs heading next.en.srt 5.0 KB
~Get Your Files Here !/058. Chapter 10. Visualizing the latent space of a ConvNet.en.srt 4.8 KB
~Get Your Files Here !/049. Chapter 9. Residual connections.en.srt 4.7 KB
~Get Your Files Here !/104. Chapter 20. Limitations of deep learning.en.srt 4.6 KB
~Get Your Files Here !/005. Chapter 1. The deep in deep learning .en.srt 4.5 KB
~Get Your Files Here !/006. Chapter 1. Understanding how deep learning works, in three figures.en.srt 4.3 KB
~Get Your Files Here !/011. Chapter 1. Summer can turn to winter.en.srt 4.3 KB
~Get Your Files Here !/012. Chapter 1. The promise of AI.en.srt 4.3 KB
~Get Your Files Here !/071. Chapter 13. Going even further.en.srt 4.0 KB
~Get Your Files Here !/068. Chapter 13. Timeseries forecasting.en.srt 3.8 KB
~Get Your Files Here !/002. Chapter 1. Artificial intelligence.en.srt 3.8 KB
~Get Your Files Here !/007. Chapter 1. Understanding how deep learning works, in three figures.en.srt 3.7 KB
~Get Your Files Here !/053. Chapter 9. Beyond convolution - Vision Transformers.en.srt 3.5 KB
~Get Your Files Here !/105. Chapter 20. What might lie ahead.en.srt 3.3 KB
~Get Your Files Here !/008. Chapter 1. The age of generative AI.en.srt 3.0 KB
~Get Your Files Here !/020. Chapter 3. How these frameworks relate to each other.en.srt 3.0 KB
~Get Your Files Here !/052. Chapter 9. Putting it together - A mini Xception-like model.en.srt 2.9 KB
~Get Your Files Here !/034. Chapter 5. Summary.en.srt 2.9 KB
~Get Your Files Here !/018. Chapter 2. Summary.en.srt 2.9 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 2.3 KB
~Get Your Files Here !/078. Chapter 14. Summary.en.srt 2.0 KB
~Get Your Files Here !/094. Chapter 17. Summary.en.srt 1.9 KB
~Get Your Files Here !/038. Chapter 6. Summary.en.srt 1.8 KB
~Get Your Files Here !/067. Chapter 12. Summary.en.srt 1.8 KB
~Get Your Files Here !/072. Chapter 13. Summary.en.srt 1.6 KB
~Get Your Files Here !/029. Chapter 4. Summary.en.srt 1.4 KB
~Get Your Files Here !/025. Chapter 3. Summary.en.srt 1.3 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

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

File List

Download Torrent

Related Resources

Copyright Infringement