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Hands-On Supervised Machine Learning with Python: Master Regression, Classification, and Predictive Modeling Using Scikit-Learn
Paperback
DatabasesGeneral ComputersProgramming
Publisher: Independently Published
Published: Feb 22 2026
Pages: 306
Weight: 0.91
Height: 0.64 Width: 6.00 Depth: 9.00
Language: English
Unlock real-world machine learning mastery with the ultimate hands-on guide using Python and Scikit-Learn!
Whether you're a beginner data scientist, aspiring ML engineer, or professional looking to build production-ready models, this book delivers practical, up-to-date skills you can apply immediately. No deep learning distractions-just focused, powerful supervised learning techniques that power most industry applications in 2026.
What you'll master:
- End-to-end projects - from data prep to deployment (churn prediction, fraud detection, and more)
- Regression & classification fundamentals - linear/logistic models, decision trees, random forests, and advanced boosting (XGBoost, LightGBM, CatBoost)
- Modern Scikit-Learn pipelines, hyperparameter tuning, and model evaluation
- Interpretability & fairness - SHAP, LIME, bias detection, and ethical deployment
- Production-ready skills - Flask/FastAPI APIs, Streamlit dashboards, and basic MLOps
With clear code, real datasets, GitHub repo, and 2026-updated best practices, you'll confidently build, explain, and deploy supervised machine learning models that deliver results.
Start building intelligent systems today - grab your copy and level up your Python ML skills!
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