Deep Learning with Python, Third Edition, Video Edition
- CategoryOther
- TypeTutorials
- LanguageEnglish
- Total size2.5 GB
- Uploaded Byfreecoursewb
- Downloads39
- Last checkedNov. 13th '25
- Date uploadedNov. 13th '25
- Seeders 5
- Leechers19
Deep Learning with Python, Third Edition, Video Edition
https://WebToolTip.com
Published 9/2025
By Matthew Watson, Francois Chollet
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Genre: eLearning | Language: English + subtitle | Duration: 17h 7m | Size: 2.5 GB
The bestselling book on Python deep learning, now covering generative AI, Keras 3, PyTorch, and JAX!
Deep Learning with Python, Third Edition puts the power of deep learning in your hands. This new edition includes the latest Keras and TensorFlow features, generative AI models, and added coverage of PyTorch and JAX. Learn directly from the creator of Keras and step confidently into the world of deep learning with Python.
In Deep Learning with Python, Third Edition you’ll discover
Deep learning from first principles
The latest features of Keras 3
A primer on JAX, PyTorch, and TensorFlow
Image classification and image segmentation
Time series forecasting
Large Language models
Text classification and machine translation
Text and image generation—build your own GPT and diffusion models!
Scaling and tuning models
Files:
[ WebToolTip.com ] Deep Learning with Python, Third Edition, Video Edition- Get Bonus Downloads Here.url (0.2 KB) ~Get Your Files Here !
- 001. Chapter 1. What is deep learning.en.srt (2.3 KB)
- 001. Chapter 1. What is deep learning.mp4 (5.0 MB)
- 002. Chapter 1. Artificial intelligence.en.srt (3.8 KB)
- 002. Chapter 1. Artificial intelligence.mp4 (7.5 MB)
- 003. Chapter 1. Machine learning.en.srt (6.1 KB)
- 003. Chapter 1. Machine learning.mp4 (12.6 MB)
- 004. Chapter 1. Learning rules and representations from data.en.srt (9.6 KB)
- 004. Chapter 1. Learning rules and representations from data.mp4 (17.0 MB)
- 005. Chapter 1. The deep in deep learning .en.srt (4.5 KB)
- 005. Chapter 1. The deep in deep learning .mp4 (9.8 MB)
- 006. Chapter 1. Understanding how deep learning works, in three figures.en.srt (4.3 KB)
- 006. Chapter 1. Understanding how deep learning works, in three figures.mp4 (6.9 MB)
- 007. Chapter 1. Understanding how deep learning works, in three figures.en.srt (3.7 KB)
- 007. Chapter 1. Understanding how deep learning works, in three figures.mp4 (7.9 MB)
- 008. Chapter 1. The age of generative AI.en.srt (3.0 KB)
- 008. Chapter 1. The age of generative AI.mp4 (4.4 MB)
- 009. Chapter 1. What deep learning has achieved so far.en.srt (2.7 KB)
- 009. Chapter 1. What deep learning has achieved so far.mp4 (6.5 MB)
- 010. Chapter 1. Beware of the short-term hype.en.srt (6.6 KB)
- 010. Chapter 1. Beware of the short-term hype.mp4 (15.1 MB)
- 011. Chapter 1. Summer can turn to winter.en.srt (4.3 KB)
- 011. Chapter 1. Summer can turn to winter.mp4 (11.0 MB)
- 012. Chapter 1. The promise of AI.en.srt (4.3 KB)
- 012. Chapter 1. The promise of AI.mp4 (8.5 MB)
- 013. Chapter 2. The mathematical building blocks of neural networks.en.srt (14.7 KB)
- 013. Chapter 2. The mathematical building blocks of neural networks.mp4 (22.2 MB)
- 014. Chapter 2. Data representations for neural networks.en.srt (17.7 KB)
- 014. Chapter 2. Data representations for neural networks.mp4 (32.6 MB)
- 015. Chapter 2. The gears of neural networks - Tensor operations.en.srt (23.8 KB)
- 015. Chapter 2. The gears of neural networks - Tensor operations.mp4 (30.7 MB)
- 016. Chapter 2. The engine of neural networks - Gradient-based optimization.en.srt (35.2 KB)
- 016. Chapter 2. The engine of neural networks - Gradient-based optimization.mp4 (60.2 MB)
- 017. Chapter 2. Looking back at our first example.en.srt (11.4 KB)
- 017. Chapter 2. Looking back at our first example.mp4 (19.3 MB)
- 018. Chapter 2. Summary.en.srt (2.9 KB)
- 018. Chapter 2. Summary.mp4 (4.5 MB)
- 019. Chapter 3. Introduction to TensorFlow, PyTorch, JAX, and Keras.en.srt (9.4 KB)
- 019. Chapter 3. Introduction to TensorFlow, PyTorch, JAX, and Keras.mp4 (20.0 MB)
- 020. Chapter 3. How these frameworks relate to each other.en.srt (3.0 KB)
- 020. Chapter 3. How these frameworks relate to each other.mp4 (5.9 MB)
- 021. Chapter 3. Introduction to TensorFlow.en.srt (21.2 KB)
- 021. Chapter 3. Introduction to TensorFlow.mp4 (35.5 MB)
- 022. Chapter 3. Introduction to PyTorch.en.srt (17.9 KB)
- 022. Chapter 3. Introduction to PyTorch.mp4 (26.9 MB)
- 023. Chapter 3. Introduction to JAX.en.srt (17.5 KB)
- 023. Chapter 3. Introduction to JAX.mp4 (27.5 MB)
- 024. Chapter 3. Introduction to Keras.en.srt (28.1 KB)
- 024. Chapter 3. Introduction to Keras.mp4 (48.3 MB)
- 025. Chapter 3. Summary.en.srt (1.3 KB)
- 025. Chapter 3. Summary.mp4 (4.0 MB)
- 026. Chapter 4. Classification and regression.en.srt (28.0 KB)
- 026. Chapter 4. Classification and regression.mp4 (47.8 MB)
- 027. Chapter 4. Classifying newswires - A multiclass classification example.en.srt (14.4 KB)
- 027. Chapter 4. Classifying newswires - A multiclass classification example.mp4 (23.6 MB)
- 028. Chapter 4. Predicting house prices - A regression example.en.srt (15.5 KB)
- 028. Chapter 4. Predicting house prices - A regression example.mp4 (25.0 MB)
- 029. Chapter 4. Summary.en.srt (1.4 KB)
- 029. Chapter 4. Summary.mp4 (2.1 MB)
- 030. Chapter 5. Fundamentals of machine learning.en.srt (32.7 KB)
- 030. Chapter 5. Fundamentals of machine learning.mp4 (51.8 MB)
- 031. Chapter 5. Evaluating machine-learning models.en.srt (14.6 KB)
- 031. Chapter 5. Evaluating machine-learning models.mp4 (25.3 MB)
- 032. Chapter 5. Improving model fit.en.srt (9.5 KB)
- 032. Chapter 5. Improving model fit.mp4 (15.7 MB)
- 033. Chapter 5. Improving generalization.en.srt (25.0 KB)
- 033. Chapter 5. Improving generalization.mp4 (40.4 MB)
- 034. Chapter 5. Summary.en.srt (2.9 KB)
- 034. Chapter 5. Summary.mp4 (6.9 MB)
- 035. Chapter 6. The universal workflow of machine learning.en.srt (30.1 KB)
- 035. Chapter 6. The universal workflow of machine learning.mp4 (60.2 MB)
- 036. Chapter 6. Developing a model.en.srt (18.5 KB)
- 036. Chapter 6. Developing a model.mp4 (31.7 MB)
- 037. Chapter 6. Deploying your model.en.srt (21.6 KB)
- 037. Chapter 6. Deploying your model.mp4 (37.9 MB)
- 038. Chapter 6. Summary.en.srt (1.8 KB)
- 038. Chapter 6. Summary.mp4 (3.9 MB)
- 039. Chapter 7. A deep dive on Keras.en.srt (5.6 KB)
- 039. Chapter 7. A deep dive on Keras.mp4 (11.0 MB)
- 040. Chapter 7. Different ways to build Keras models.en.srt (20.2 KB)
- 040. Chapter 7. Different ways to build Keras models.mp4 (32.5 MB)
- 041. Chapter 7. Using built-in training and evaluation loops.en.srt (14.7 KB)
- 041. Chapter 7. Using built-in training and evaluation loops.mp4 (24.6 MB)
- 042. Chapter 7. Writing your own training and evaluation loops.en.srt (23.7 KB)
- 042. Chapter 7. Writing your own training and evaluation loops.mp4 (38.6 MB)
- 043. Chapter 7. Summary.en.srt (1.3 KB)
- 043. Chapter 7. Summary.mp4 (4.0 MB)
- 044. Chapter 8. Image classification.en.srt (27.0 KB)
- 044. Chapter 8. Image classification.mp4 (47.7 MB)
- 045. Chapter 8. Training a ConvNet from scratch on a small dataset.en.srt (27.4 KB)
- 045. Chapter 8. Training a ConvNet from scratch on a small dataset.mp4 (48.3 MB)
- 046. Chapter 8. Using a pretrained model.en.srt (23.6 KB)
- 046. Chapter 8. Using a pretrained model.mp4 (42.4 MB)
- 047. Chapter 8. Summary.en.srt (1.1 KB)
- 047. Chapter 8. Summary.mp4 (2.9 MB)
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