SEBASTIAN RASCHKA / YUXI (HAYDEN) LIU / VAHID MIRJALILI / DMYTRO DZHULGAKOV
U$ 82,02 84,07 €
U$ 82,02 84,07 €
u003cpu003eThis book of the bestselling and widely acclaimed Python Machine Learning series is a comprehensive guide to machine and deep learning using PyTorch's simple to code frameworku003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eKey Features: u003c/pu003eu003culu003eu003cliu003eLearn applied machine learning with a solid foundation in theoryu003c/liu003eu003cliu003eClear, intuitive explanations take you deep into the theory and practice of Python machine learningu003c/liu003eu003cliu003eFully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practicesu003c/liu003eu003c/ulu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eBook Description: u003c/pu003eu003cpu003eMachine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial and a reference you'll keep coming back to as you build your machine learning systems.u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003ePacked with clear explanations, visualizations, and examples, the book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach the principles allowing you to build models and applications for yourself.u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eWhy PyTorch?u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003ePyTorch is the Pythonic way to learn machine learning, making it easier to learn and simpler to code with. This book explains the essential parts of PyTorch and how to create models using popular libraries, such as PyTorch Lightning and PyTorch Geometric.u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eYou will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is expanded to cover the latest trends in deep learning, including graph neural networks and large-scale transformers used for natural language processing (NLP).u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eThis PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eWhat You Will Learn: u003c/pu003eu003culu003eu003cliu003eExplore frameworks, models, and techniques for machines to 'learn' from datau003c/liu003eu003cliu003eUse scikit-learn for machine learning and PyTorch for deep learningu003c/liu003eu003cliu003eTrain machine learning classifiers on images, text, and moreu003c/liu003eu003cliu003eBuild and train neural networks, transformers, and boosting algorithmsu003c/liu003eu003cliu003eDiscover best practices for evaluating and tuning modelsu003c/liu003eu003cliu003ePredict continuous target outcomes using regression analysisu003c/liu003eu003cliu003eDig deeper into textual and social media data using sentiment analysisu003c/liu003eu003c/ulu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eWho this book is for: u003c/pu003eu003cpu003eThis book is for incident responders, digital forensic specialists, cybersecurity analysts, system administrators, malware analysts, students, and curious security professionals If you know some Python and you want to use machine learning and deep learning, pick up this book. Whether you want to start from scratch or extend your machine learning knowledge, this is an essential resource.u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eWritten for developers and data scientists who want to create practical machine learning with Python and PyTorch deep learning code. This Python book is ideal for anyone who wants to teach computers how to learn from data.u003c/pu003eu003cpu003eu003cbru003eu003c/pu003eu003cpu003eWorking knowledge of the Python programming language, along with a good understanding of calculus and linear algebra is a must.
