Dash10107/learn-ml-by-doing

A well-organized collection of Jupyter notebooks covering the full machine learning journey—from data preprocessing and classic algorithms to deep learning, NLP, and reinforcement learning. Ideal for learners and professionals to explore, experiment, and master ML with real code.

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This collection helps data science learners and professionals understand and apply machine learning. It takes raw or structured datasets and guides you through the process of cleaning, transforming, and building predictive models. If you're a data analyst, aspiring data scientist, or someone looking to incorporate machine learning into your work, these notebooks offer practical, hands-on examples.

No commits in the last 6 months.

Use this if you want to learn machine learning concepts by directly working with code and real-world examples, from basic data preparation to advanced topics like deep learning and reinforcement learning.

Not ideal if you're looking for a theoretical textbook without hands-on coding, or if you need an out-of-the-box solution to deploy a specific machine learning model without understanding its inner workings.

data science education machine learning practice predictive analytics natural language processing data preprocessing
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 4 / 25
Maturity 15 / 25
Community 13 / 25

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8

Forks

2

Language

Jupyter Notebook

License

MIT

Last pushed

Oct 06, 2025

Commits (30d)

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