Build Smarter Software with Machine Learning—Without Starting from Zero
If you’re a programmer who wants to break into artificial intelligence, Machine Learning for Programmers is your fast track. This book skips the math-heavy theory and goes straight into building intelligent, real-world applications using Python.
Designed for developers, not data scientists, this guide focuses on practical implementation: loading data, training models, testing predictions, and deploying ML systems using tools you already know—like Python, scikit-learn, and TensorFlow.
What You'll Learn:Core ML concepts made simple for coders
How to build classification, regression, and clustering models
Real-world projects: spam filters, recommendation engines, and more
Step-by-step tutorials using Python and popular ML libraries
Data preparation and feature engineering explained clearly
Hyperparameter tuning, model evaluation, and cross-validation
The basics of neural networks and deep learning
How to deploy models into live applications and services
Best practices for clean, testable, production-ready ML code
You don’t need a PhD to get started—just Python skills and a problem to solve.
Code smarter. Think in models. Build the future.
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PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000. Nº de ref. del artículo: L2-9798290084473
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Paperback. Condición: new. Paperback. Build Smarter Software with Machine Learning-Without Starting from ZeroIf you're a programmer who wants to break into artificial intelligence, Machine Learning for Programmers is your fast track. This book skips the math-heavy theory and goes straight into building intelligent, real-world applications using Python.Designed for developers, not data scientists, this guide focuses on practical implementation: loading data, training models, testing predictions, and deploying ML systems using tools you already know-like Python, scikit-learn, and TensorFlow.What You'll Learn: Core ML concepts made simple for codersHow to build classification, regression, and clustering modelsReal-world projects: spam filters, recommendation engines, and moreStep-by-step tutorials using Python and popular ML librariesData preparation and feature engineering explained clearlyHyperparameter tuning, model evaluation, and cross-validationThe basics of neural networks and deep learningHow to deploy models into live applications and servicesBest practices for clean, testable, production-ready ML codeYou don't need a PhD to get started-just Python skills and a problem to solve.Code smarter. Think in models. Build the future. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798290084473
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