Neurojedi/Machine-Learning-Zero2Hero

A series of notebooks that introduce Machine Learning concepts with hands-on practice and its mathematics in brief.

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This project offers a collection of Jupyter notebooks designed to help you deepen your understanding of machine learning algorithms. Each notebook combines the mathematical theory behind an algorithm with hands-on Python code examples and practical exercises on various datasets. This resource is ideal for data scientists, analysts, or students who already have a basic grasp of machine learning concepts and want to strengthen their theoretical knowledge and implementation skills.

No commits in the last 6 months.

Use this if you are a data professional or student who wants to understand both the 'how' (coding) and 'why' (mathematics) of machine learning algorithms through practical examples.

Not ideal if you are an absolute beginner to machine learning with no prior exposure to algorithms or programming concepts, as these notebooks assume some foundational knowledge.

data-science machine-learning-education algorithm-explanation data-analysis predictive-modeling
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 8 / 25

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87

Forks

5

Language

Jupyter Notebook

License

MIT

Last pushed

Jul 20, 2023

Commits (30d)

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