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  1. Tutorials
  2. Deep Learning Tutorial

Deep Learning Tutorial

Build neural networks from scratch in NumPy, then train real models in PyTorch, from the perceptron to CNNs, transformers and a full project.

30 free lessons Intermediate to Advanced Covers PyTorch 2.15 with NumPy from-scratch examples

Start the first lesson

Getting Started Intermediate

  1. 1Deep Learning Introduction
  2. 2The Neuron & the Perceptron
  3. 3Activation Functions
  4. 4Layers & the Forward Pass
  5. 5Loss Functions

How Networks Learn Intermediate

  1. 6Gradient Descent
  2. 7Backpropagation Step by Step
  3. 8A Two-Layer Network from Scratch
  4. 9Training Loops, Batches & Epochs
  5. 10Optimisers: SGD, Momentum & Adam
  6. 11Weight Initialisation

Training Better Networks Intermediate

  1. 12Overfitting & Regularisation
  2. 13Batch Normalisation

PyTorch Advanced

  1. 14PyTorch Tensors
  2. 15Autograd
  3. 16Building Models with nn.Module
  4. 17Datasets & DataLoaders
  5. 18A Full PyTorch Training Loop
  6. 19GPU Basics

Network Architectures Advanced

  1. 20Convolution & Pooling
  2. 21CNN Architectures: LeNet to ResNet
  3. 22Transfer Learning
  4. 23RNNs, LSTMs & GRUs
  5. 24Embeddings
  6. 25Attention & Transformers

Deep Learning in Practice Advanced

  1. 26Saving & Loading Models
  2. 27Evaluating & Debugging Training
  3. 28Deployment: torch.export, TorchScript & ONNX
  4. 29Responsible Deep Learning
  5. 30Project: Image Classifier End to End

Learn Deep Learning with a mentor

Free lessons get you started. Our Data Science & Machine Learning training adds real projects and code reviews from working developers.

  • Project-based learning
  • Mentor code reviews
  • Free counselling call
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