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Deep Learning

Neural networks and the ideas behind modern AI, vision and language, layer by layer.

21 lessons about 7 hours Medium
Learn it by writing it.

Every lesson runs real code in your browser, checked the moment you submit. No installing anything, no setup, no waiting.

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What this course covers

  1. What is Deep Learning?
  2. Neural Networks: Brain in Code
  3. How a Neuron Computes
  4. Activation Functions
  5. Deep Learning: Stacked Brains
  6. Layer by Layer: The Forward Pass
  7. Loss Functions: Measuring How Wrong
  8. How a Network Learns: Gradient Descent
  9. Backpropagation: Tracing Blame Backward
  10. The Training Loop: Putting It Together
  11. Learning Rate, Epochs and Batches
  12. Overfitting in Deep Learning: Dropout and More
  13. Convolutions: How AI Sees Features
  14. Computer Vision: Teaching AI to See
  15. Embeddings: Turning Things into Vectors
  16. NLP: How Computers Understand Text
  17. Transfer Learning: Stand on Giants' Shoulders
  18. Capstone: Train a Tiny Network from Scratch
  19. CNN Architecture and Pooling
  20. Sequences and Memory: RNNs and LSTMs
  21. Transformers and Attention

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