Advanced TensorFlow - Custom Training and Optimization

  • CategoryOther
  • TypeTutorials
  • LanguageEnglish
  • Total size512.9 MB
  • Uploaded Byfreecoursewb
  • Downloads36
  • Last checkedApr. 17th '26
  • Date uploadedApr. 17th '26
  • Seeders 10
  • Leechers6

Infohash : E7979CF734A16B056146877610806380217CA399

Advanced TensorFlow: Custom Training and Optimization

https://WebToolTip.com

Released 4/2026
By Ashraf AlMadhoun
MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 Ch
Level: Advanced | Genre: eLearning | Language: English + subtitle | Duration: 3h 18m 19s | Size: 547 MB

Production ML often requires training behavior that the standard Keras workflow cannot express cleanly.

What you'll learn
Production ML often requires training behavior that the standard Keras workflow cannot express cleanly. In this course, Advanced TensorFlow: Custom Training and Optimization, you’ll gain the ability to implement and debug custom training systems that scale. First, you’ll explore custom training loops with tf.GradientTape, including gradient transformations, learning rate schedules, mixed precision, and advanced regularization. Next, you’ll discover how to build custom layers, models, losses, metrics, optimizers, and custom train_step() implementations for specialized procedures. Finally, you’ll learn how to scale training with TensorFlow distribution strategies and apply these patterns to advanced architectures and workflows like GNNs, VAEs, GANs, reinforcement learning, and scikit-learn integration. When you’re finished with this course, you’ll have the skills and knowledge needed to build production-ready TensorFlow training pipelines with full control over optimization and execution.

Files:

[ WebToolTip.com ] Advanced TensorFlow - Custom Training and Optimization
  • Get Bonus Downloads Here.url (0.2 KB)
  • ~Get Your Files Here ! 01. Custom Training Loops The Production Baseline
    • 01. When Model.fit() Isn’t Enough.mp4 (10.6 MB)
    • 01. When Model.fit() Isn’t Enough.srt (6.9 KB)
    • 02. Building the Complete GradientTape Loop.mp4 (8.3 MB)
    • 02. Building the Complete GradientTape Loop.srt (5.9 KB)
    • 03. Correctness Conditions of a Custom Training Step.mp4 (5.0 MB)
    • 03. Correctness Conditions of a Custom Training Step.srt (3.6 KB)
    • 04. Demo Train a Small Network End-to-end.mp4 (18.5 MB)
    • 04. Demo Train a Small Network End-to-end.srt (6.4 KB)
    02. Optimization Controls Clipping and Schedules
    • 01. Why Training Becomes Unstable.mp4 (7.1 MB)
    • 01. Why Training Becomes Unstable.srt (5.6 KB)
    • 02. Implement Gradient Clipping and LR Schedules.mp4 (12.1 MB)
    • 02. Implement Gradient Clipping and LR Schedules.srt (7.8 KB)
    • 03. Tuning and Validating Stabilizers in Production.mp4 (15.1 MB)
    • 03. Tuning and Validating Stabilizers in Production.srt (8.5 KB)
    • 04. Demo Stabilize Training with Clipping and Schedule.mp4 (31.3 MB)
    • 04. Demo Stabilize Training with Clipping and Schedule.srt (10.2 KB)
    03. Advanced Loop Techniques Mixed Precision and Nested Tape
    • 01. Mixed Precision Mechanics That Matter.mp4 (7.5 MB)
    • 01. Mixed Precision Mechanics That Matter.srt (5.2 KB)
    • 02. Nested GradientTape.mp4 (5.7 MB)
    • 02. Nested GradientTape.srt (4.7 KB)
    • 03. Engineering Pattern Safe Mixed Precision and Nested Tape.mp4 (18.1 MB)
    • 03. Engineering Pattern Safe Mixed Precision and Nested Tape.srt (10.0 KB)
    • 04. Demo Mixed Precision with Gradient Penalty.mp4 (28.6 MB)
    • 04. Demo Mixed Precision with Gradient Penalty.srt (10.8 KB)
    04. Custom Layers and Models Subclassing for Real Architectures
    • 01. When to Subclass Layer and Model.mp4 (7.6 MB)
    • 01. When to Subclass Layer and Model.srt (5.7 KB)
    • 02. Implement Custom Components.mp4 (3.8 MB)
    • 02. Implement Custom Components.srt (3.5 KB)
    • 03. Production Readiness Tracking and Saving Subclassed Components.mp4 (17.8 MB)
    • 03. Production Readiness Tracking and Saving Subclassed Components.srt (9.9 KB)
    • 04. Demo Plug Custom Components into Training Part One.mp4 (26.5 MB)
    • 04. Demo Plug Custom Components into Training Part One.srt (12.4 KB)
    • 05. Demo Plug Custom Components into Training Part Two.mp4 (23.7 MB)
    • 05. Demo Plug Custom Components into Training Part Two.srt (9.7 KB)
    05. Custom Training Components Losses, Metrics, Optimizers, and train_step()
    • 01. Designing Custom Losses and Metrics.mp4 (13.7 MB)
    • 01. Designing Custom Losses and Metrics.srt (8.7 KB)
    • 02. Custom Optimizers and train_step().mp4 (6.6 MB)
    • 02. Custom Optimizers and train_step().srt (6.1 KB)
    • 03. Validating Custom Components before You Trust Them.mp4 (22.3 MB)
    • 03. Validating Custom Components before You Trust Them.srt (14.1 KB)
    • 04. Demo Specialized Training with train_step().mp4 (42.9 MB)
    • 04. Demo Specialized Training with train_step().srt (16.3 KB)
    06. Distributed Training Strategies That Ship
    • 01. Strategy Selection and Trade-offs.mp4 (6.4 MB)
    • 01. Strategy Selection and Trade-offs.srt (4.6 KB)
    • 02. Correctness and Performance in Distributed Training.mp4 (12.5 MB)
    • 02. Correctness and Performance in Distributed Training.srt (8.1 KB)
    • 03. Converting Code to Distributed Execution.mp4 (3.3 MB)
    • 03. Converting Code to Distributed Execution.srt (2.5 KB)
    • 04. Demo Distributed Custom Loop Part One.mp4 (30.2 MB)
    • 04. Demo Distributed Custom Loop Part One.srt (10.8 KB)
    • 05. Demo Distributed Custom Loop Part Two.mp4 (26.7 MB)
    • 05. Demo Distributed Custom Loop Part Two.srt (8.2 KB)
    07. Architecture Spotlights GNNs, VAEs, GANs, RL, and scikit-learn Integration
    • 01. Pattern Map for Advanced Workflows.mp4 (5.2 MB)
    • 01. Pattern Map for Advanced Workflows.srt (3.1 KB)
    • 02. Architecture-driven Training Step Patterns.mp4 (8.0 MB)
    • 02. Architecture-driven Training Step Patterns.srt (4.3 KB)
    • 03. Building GNN Layers and Models.mp4 (3.0 MB)
    • 03. Building GNN Layers and Models.srt (1.8 KB)
    • 04. VAEs and GANs with Custom Loops.mp4 (2.6 MB)
    • 04. VAEs and GANs with Custom Loops.srt (1.6 KB)
    • 05. Demo RL Loop and Scikit-learn Integration–Part One.mp4 (34.1 MB)
    • 05. Demo RL Loop and Scikit-learn Integration–Part One.srt (10.8 KB)
    • 06. Demo RL Loop and Scikit-learn Integration–Part Two.mp4 (47.9 MB)
    • 06. Demo RL Loop and Scikit-learn Integration–Part Two.srt (14.8 KB)
    • Bonus Resources.txt (0.1 KB)

Code:

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