now

learning machine learning and deep learning through hands-on coursework and implementation.

• end-to-end machine learning with scikit-learn
• regression, classification, SVMs, trees, and ensemble methods
• model evaluation, regularization, and feature selection
• deep learning models: CNNs, RNNs, LSTMs, and transformers
• generative models: autoencoders, GANs, diffusion models, and LLM fine-tuning

Hands-On Machine Learning with Scikit-Learn & PyTorch — Aurélien Géron

cutting down on distractions, maintaining a personal knowledge base, and playing games.