salma2vec/ML-Beginner-Portfolio

Kickstart ML through these 20+ foundational projects; Kaggle datasets, problem statements and comprehensive EDA (Exploratory Data Analysis) walkthroughs.

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Emerging

This collection helps aspiring data scientists and machine learning engineers practice core skills. You get practical problem statements, relevant datasets (like X-ray images, movie ratings, or real estate figures), and step-by-step guides for exploring data and building models. It's designed for individuals looking to build a portfolio of hands-on machine learning projects.

No commits in the last 6 months.

Use this if you are a beginner in machine learning and want to build practical projects to understand concepts and create a portfolio.

Not ideal if you are an experienced machine learning practitioner looking for advanced research problems or ready-to-deploy solutions.

data-science-education machine-learning-practice exploratory-data-analysis model-building project-portfolio
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 4 / 25
Maturity 16 / 25
Community 13 / 25

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Stars

8

Forks

2

Language

Jupyter Notebook

License

GPL-3.0

Last pushed

Nov 05, 2023

Commits (30d)

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