rohanmistry231/Complete-Machine-Learning-With-Real-World-Deployment

A comprehensive guide to machine learning with Python, covering algorithms, model training, and real-world deployment using frameworks like Scikit-learn and Flask. Includes end-to-end projects with datasets and tutorials for building and deploying ML applications.

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This collection of notes and projects helps aspiring data scientists and machine learning engineers learn to build and deploy real-world machine learning applications. It takes you from foundational Python skills and ML concepts to hands-on projects, showing how to transform raw data into predictive models for tasks like flight fare forecasting, mushroom classification, and toxic comment identification. You'll gain practical experience in turning data into actionable insights and deployable solutions.

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Use this if you are a beginner looking for a structured, end-to-end learning path to become proficient in machine learning, from theory to practical deployment.

Not ideal if you are an experienced machine learning practitioner seeking advanced research topics or production-ready infrastructure solutions.

data-science-education machine-learning-projects predictive-modeling model-deployment time-series-forecasting
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 7 / 25
Maturity 16 / 25
Community 0 / 25

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Jupyter Notebook

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MIT

Last pushed

May 23, 2025

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