The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. Perhaps you're ready to jump in, but you're unsure where or how to begin. Whether you're looking to enhance your skill set and apply machine learning to real-world projects or are simply curious about how AI systems function, this book is your jumping-off place.In a way that's approachable yet deeply informative, author Aurelien Geron delivers the ultimate introductory guide to machine learning and deep learning. With a focus on clear explanations and real-world Python examples, the book takes you through cutting-edge tools like scikit-learn and PyTorch-from basic regression techniques to advanced neural networks like transformers and generative adversarial networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to begin building intelligent systems.
Understand ML basics, including concepts like overfitting and hyperparameter tuning
Learn to build end-to-end ML projects using scikit-learn, from data exploration to model evaluation
Explore advanced architectures like convolutional and recurrent neural networks with PyTorch
Discover techniques for unsupervised learning, such as clustering and anomaly detection
Increase your expertise in state-of-the-art AI systems by fine-tuning pretrained models
Build tangible skills with complete hands-on coding exercises and real-world applications
Sprache
Verlagsort
Zielgruppe
Maße
Höhe: 233 mm
Breite: 175 mm
Dicke: 48 mm
Gewicht
ISBN-13
979-8-3416-0798-9 (9798341607989)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Aurelien Geron is a Machine Learning consultant. A former Googler, he led YouTube's video classification team from 2013 to 2016. He was also a founder and CTO of Wifirst from 2002 to 2012, a leading Wireless ISP in France, and a founder and CTO of Polyconseil in 2001, a telecom consulting firm. Before this he worked as an engineer in a variety of domains: finance (JP Morgan and Societe Generale), defense (Canada's DOD), and healthcare (blood transfusion). He published a few technical books (on C++, WiFi, and Internet architectures), and was a Computer Science lecturer in a French engineering school.