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Machine Learning Intermediate

PyTorch Essentials

A COMPLETE beginner-to-advanced PyTorch Deep Learning course. Learn tensors, CNNs, NLP, and model deployment using PyTorch.

20 chapters 2h 4m 4.7 (205)
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What you'll learn

  • Introduction to Deep Learning and PyTorch
  • Setting Up Python and PyTorch Environment
  • Python Basics for AI and Deep Learning
  • NumPy, Pandas, and Data Handling
  • Understanding Neural Networks
  • PyTorch Tensors and Tensor Operations
  • Building Your First Neural Network in PyTorch
  • Activation Functions and Loss Functions

Course content

20 chapters · 2h 4m
  1. 1 Introduction to Deep Learning and PyTorch 7 min
  2. 2 Setting Up Python and PyTorch Environment 7 min
  3. 3 Python Basics for AI and Deep Learning 6 min
  4. 4 NumPy, Pandas, and Data Handling 6 min
  5. 5 Understanding Neural Networks 6 min
  6. 6 PyTorch Tensors and Tensor Operations 6 min
  7. 7 Building Your First Neural Network in PyTorch 6 min
  8. 8 Activation Functions and Loss Functions 7 min
  9. 9 Training and Evaluating Models in PyTorch 6 min
  10. 10 PyTorch Datasets and DataLoaders 7 min
  11. 11 Image Classification with CNNs in PyTorch 6 min
  12. 12 Transfer Learning with Pretrained Models 6 min
  13. 13 Natural Language Processing Basics with PyTorch 6 min
  14. 14 Recurrent Neural Networks (RNN) 6 min
  15. 15 LSTM and Sequence Models 7 min
  16. 16 Saving, Loading, and Deploying PyTorch Models 6 min
  17. 17 PyTorch Lightning and Training Optimization 6 min
  18. 18 Hyperparameter Tuning and Optimization 6 min
  19. 19 Performance Optimization and GPU Training 6 min
  20. 20 Final Project - Build Real-World AI Applications 5 min