Presentation titled "Self-taught Learning: Transfer Learning from Unlabeled Data" for Knowledge Discovery course at Ryerson University

A 6-page printable set designed for self-taught machine learning learners who want a clear path and a faster study loop. Includes a visual stage-by-stage curriculum roadmap, math and Python syntax reference sheets, a model selection guide, hyperparameter tuning cheatsheet, and a progress tracker you can reuse every week. Print once, pin them up, an

A complete Notion operating system built for self-taught ML engineers following Karpathy-style, from-scratch curricula. Track every build, experiment, paper, and concept in one organized workspace. Designed to take you from micrograd to nanoGPT and beyond — without losing the thread.