ML/DS education / course materials
All course materials for the Zero to Mastery Machine Learning and Data Science course, including notebooks, code, and datasets.
Same problem, same approach. Swapping one for another is a config change, not a rewrite.
An actively maintained, free cohort-based ML engineering course that can replace the Zero to Mastery materials.
Learn ML engineering for free in 4 months! Register here 👇🏼
An actively maintained open ML course with assignments and community, a strong current alternative to the seed.
Open Machine Learning Course
An earlier or more limited way to do the job. Still the right call when you need something small, proven, or CPU-only.
An older but comprehensive fastai/PyTorch deep-learning course; useful if you prefer that teaching style and don't need recent updates.
The fastai book, published as Jupyter Notebooks
Older TensorFlow deep-learning tutorials; a dated but valid resource for a TF-centric learning path.
This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.
Classic Coursera Data Science Specialization materials; good for an R-based, structured intro despite being stale.
Course materials for the Data Science Specialization: https://www.coursera.org/specialization/jhudatascience/1
Older ready-to-use TensorFlow tutorials; useful if you specifically want a TF tutorial archive.
:satellite: Simple and ready-to-use tutorials for TensorFlow
A large but stale data-science materials collection; useful if you want a grab-bag of notes and code rather than a structured course.
These projects were analysed and named zero-to-mastery-ml among their alternatives. The relationship is not symmetric — how zero-to-mastery-ml rates them is a separate judgement, made when zero-to-mastery-ml is analysed in its own right.
calls zero-to-mastery-ml “Choose it for a beginner data-science/ML course, but note it is older and lacks MLOps depth.”
Learn ML engineering for free in 4 months! Register here 👇🏼
calls zero-to-mastery-ml “Choose if you prefer the Zero to Mastery ML/DS syllabus, but the materials are over 18 months without updates.”
Machine Learning Course, Sharif University of Technology