Jupyter Notebooks

Interactive notebooks demonstrating key ML concepts with code and visualizations

Interactive Linear Regression

Visualize gradient descent, cost functions, and learning rate effects in real-time

Gradient DescentCost Functions3D VisualizationLearning Rates

Libraries used:

numpymatplotlibipywidgets
Beginner15 min

Neural Network from Scratch

Build a complete neural network using only NumPy with forward and backward propagation

BackpropagationActivation FunctionsWeight InitializationMini-batch SGD

Libraries used:

numpymatplotlibsklearn
Intermediate30 min

CNN Filter Visualization

Explore convolutional neural networks by visualizing learned filters and feature maps

ConvolutionFeature MapsFilter VisualizationPooling

Libraries used:

numpymatplotlibscipyPIL
Intermediate25 min

Transformer Attention Patterns

Understand self-attention mechanism with interactive visualizations

Self-AttentionMulti-Head AttentionPositional EncodingToken Embeddings

Libraries used:

numpymatplotlibseaborn
Advanced40 min

GAN for MNIST Generation

Soon

Train a GAN to generate handwritten digits with training visualizations

GeneratorDiscriminatorAdversarial TrainingMode Collapse

Libraries used:

tensorflowkerasnumpymatplotlib
Advanced45 min

Q-Learning Maze Solver

Soon

Implement Q-learning algorithm to solve maze navigation problems

Q-TableExploration vs ExploitationBellman EquationPolicy

Libraries used:

numpymatplotlibgym
Intermediate20 min

SVM Kernel Trick Visualization

Soon

Explore how the kernel trick empowers SVMs to handle non-linear separation in higher dimensions

Kernel FunctionsRBF KernelPolynomial KernelFeature Space Mapping

Libraries used:

numpymatplotlibsklearnipywidgets
Intermediate35 min

Variational Autoencoder (VAE)

Soon

Build and visualize a VAE, exploring latent space representations and generation capabilities

Encoder-DecoderLatent SpaceKL DivergenceReconstruction Loss

Libraries used:

pytorchtorchvisionnumpymatplotlibseaborn
Advanced50 min