Machine Learning in Python Made Simple: A Beginner’s Practical Guide to scikit-learn, PyTorch & Real-World ML Projects

by Hollis Denning

Machine Learning in Python Made Simple
A Beginner’s Practical Guide to scikit-learn, PyTorch & Real-World ML ProjectsUnlock the full power of modern machine-learning—no PhD requiredAre you overwhelmed by jargon-heavy textbooks and outdated tutorials?
This book is your fast-track, hands-on roadmap from absolute beginner to production-ready machine-learning engineer—written for 2025 and beyond.What makes this book different?All-in-One Journey – Data wrangling, classic algorithms, deep learning with PyTorch 3.x, deployment, MLOps, monitoring, and responsible-AI—all in one volume.Project-First Approach – Every concept is anchored by code snippets, mini-projects, and a capstone end-to-end Churn Predictor you’ll deploy to the cloud.Zero Assumptions – Starts at Python basics, then layers complexity only when you’re ready—perfect for self-taught coders or non-CS graduates.2025-Ready Toolchain – scikit-learn 1.7, PyTorch 3.x, FastAPI, Optuna, MLflow, DVC, Prometheus, and more—exactly what employers use right now.Built-In Troubleshooting – Appendices packed with error glossaries, metric tables, conda & Docker quick-starts, and community resources keep you unblocked.Inside you’ll learn Set Up Fast – Clean Python & Conda environments without dependency hell.Wrangle Data Like Pro – CSV → Parquet, missing-value tricks, pandas EDA, five-line audit scripts.Master Classic ML – Pipelines, cross-validation, hyperparameter tuning with GridSearchCV & Optuna.Dive into Deep Learning – PyTorch tensors, training loops, transfer learning in 30 minutes.Deploy for the Real World – FastAPI REST APIs, Docker containers, GitHub Actions CI/CD, zero-downtime updates.Monitor & Govern – Prometheus dashboards, SHAP explainability, Fairlearn bias audits, differential-privacy basics.Plan Your Career – Portfolio roadmaps, certification advice, next-step learning paths.Who is this book for?Absolute beginners who learn best by building.Analysts & data professionals transitioning to machine learning.Bootcamp & university students needing a one-stop practical companion.Developers & engineers who want production skills, not just notebook demos.You’ll build and A Housing-Price Regressor with scikit-learn pipelinesAn Image Classifier via transfer learning (ResNet & ViT)A Sentiment Analysis API with FastAPI + TorchScriptA full Customer-Churn Predictor pipeline from data to Prometheus-monitored microserviceStop copying disconnected code snippets.
Start creating real ML products—today.

248 pages, Kindle Edition

Published July 6, 2025