hands on supervised machine learning de turing leo (4 resultados)

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Paperback. Condición: new. Paperback. 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 evaluationInterpretability & fairness - SHAP, LIME, bias detection, and ethical deploymentProduction-ready skills - Flask/FastAPI APIs, Streamlit dashboards, and basic MLOpsWith 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! This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Paperback. Condición: new. Paperback. 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 evaluationInterpretability & fairness - SHAP, LIME, bias detection, and ethical deploymentProduction-ready skills - Flask/FastAPI APIs, Streamlit dashboards, and basic MLOpsWith 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! This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.