Machine Learning Tutorials

Build your first neural network from scratch using NumPy. Understand the fundamentals of forward propagation, backpropagation, and gradient descent.

Create a convolutional neural network for image classification using PyTorch. Train on CIFAR-10 and learn about data augmentation techniques.

Fine-tune pre-trained transformer models for text classification. Learn about attention mechanisms and the Hugging Face ecosystem.

Predict future values using LSTM networks. Work with real-world stock market data and learn about sequence modeling.

Implement Q-learning to train an agent in OpenAI Gym environments. Understand the core concepts of RL and policy optimization.

Build a Generative Adversarial Network to create synthetic images. Explore DCGAN architecture and training stability techniques.