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SKU/Artículo: AMZ-B0FGZ8M63K

Machine Learning 101 : From Linear Regression to Neural Networks, A Beginner’s Guide

Format:

Kindle

Hardcover

Kindle

Paperback

Detalles del producto

Disponibilidad:
Fuera de stock

Peso con empaque:
0.97 kg

Devolución:
No

Condición
Nuevo

Producto de:
Amazon

Viaja desde
USA

Sobre este producto

Curious about machine learning but not sure where to begin? This book was made for you.Machine Learning 101 is a clear, beginner-friendly guide that takes you from your first model to more advanced topics like neural networks—without overwhelming math or jargon. Whether you're a student, a developer, or just tech-curious, this book walks you through the core ideas and practical tools used in machine learning today.You'll explore step-by-step how machines "learn" from data using real Python examples and simple explanations. No prior experience in data science or AI is required—just a willingness to follow along.In this guide, you’ll learn:What machine learning is—and what it isn’tHow to prepare data for training and testingThe basics of linear and logistic regressionWorking with decision trees, k-nearest neighbors, and SVMsHow clustering and dimensionality reduction workBuilding simple neural networks from scratchHow to evaluate models with metrics like accuracy, precision, and recallWhere to go next with libraries like scikit-learn, TensorFlow, and PyTorchWith real-world examples and hands-on code, you’ll gain practical skills and a solid foundation that will set you up for more advanced learning.Machine Learning 101 doesn’t assume a PhD in math or computer science—it’s your friendly, guided introduction to one of the most powerful fields in tech today.

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