Machine Learning Con Pytorch Y Scikit Lean
Download Machine Learning Con Pytorch Y Scikit Lean PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Machine Learning Con Pytorch Y Scikit Lean book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages.
Machine Learning with PyTorch and Scikit-Learn
Author: Sebastian Raschka
language: en
Publisher: Packt Publishing Ltd
Release Date: 2022-02-25
This 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 framework. Purchase of the print or Kindle book includes a free eBook in PDF format. Key Features Learn applied machine learning with a solid foundation in theory Clear, intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover PyTorch, transformers, XGBoost, graph neural networks, and best practices Book DescriptionMachine 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. Packed 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. Why PyTorch? PyTorch 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. You 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). This 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.What you will learn Explore frameworks, models, and techniques for machines to learn from data Use scikit-learn for machine learning and PyTorch for deep learning Train machine learning classifiers on images, text, and more Build and train neural networks, transformers, and boosting algorithms Discover best practices for evaluating and tuning models Predict continuous target outcomes using regression analysis Dig deeper into textual and social media data using sentiment analysis Who this book is for If you have a good grasp of Python basics and want to start learning about machine learning and deep learning, then this is the book for you. This is an essential resource written for developers and data scientists who want to create practical machine learning and deep learning applications using scikit-learn and PyTorch. Before you get started with this book, you’ll need a good understanding of calculus, as well as linear algebra.
Machine Learning Con Pytorch Y Scikit Lean
Si busca un manual de referencia sobre Machine Learning y Deep Learning con PyTorch, ha llegado al libro indicado. En él se explica paso a paso cómo construir sistemas de aprendizaje automático con éxito.Mientras que en algunos libros solo se enseña a seguir instrucciones, en este descubrirá los principios para crear modelos y aplicaciones por sí mismo. Encontrará multitud de explicaciones claras, visualizaciones y ejemplos, y aprenderá en profundidad todas las técnicas esenciales de Machine Learning.Actualizado para ocuparse de Machine Learning utilizando PyTorch, este libro también presenta las últimas incorporaciones a Scikit-Learn. Además, trata varias técnicas de Machine Learning y Deep Learning para la clasificación de textos e imágenes. Con este libro, también aprenderá sobre las redes generativas antagónicas (GAN), útiles para generar nuevos datos y entrenar agentes inteligentes con aprendizaje reforzado.Por último, esta edición incluye las últimas tendencias en Machine Learning, como las introducciones a las redes neuronales de grafos y transformadores a gran escala utilizados para el procesamiento del lenguaje natural (NLP).Sin duda, tanto si es un desarrollador de Python neófito en Machine Learning como si desea profundizar en los últimos avances, este libro de PyTorch será su gran aliado en el aprendizaje automático con Python.
Scikit-Learn Unleashed: A Comprehensive Guide to Machine Learning with Python
"Scikit-Learn Unleashed: A Comprehensive Guide to Machine Learning with Python" is your ultimate roadmap to mastering one of Python's most robust machine learning libraries. This guide is perfect for those beginning their journey into machine learning as well as seasoned experts looking to broaden their expertise and refine their techniques. Spanning ten meticulously crafted chapters, this book delves deep into Scikit-Learn's extensive offerings, from foundational concepts to advanced applications. You'll begin your journey with essential machine learning principles and data preprocessing, before advancing to explore both supervised and unsupervised learning techniques. The book also offers insightful guidance on advanced model tuning and customization to ensure an all-encompassing understanding of machine learning. Every chapter is a stepping stone, building on prior knowledge to introduce complex ideas seamlessly with real-world examples that bring theoretical concepts to life. You'll learn to tackle data preprocessing challenges, apply diverse regression and classification algorithms, harness the potential of unsupervised learning, and enhance model performance through ensemble techniques. Moreover, the book covers essential topics like managing text data, model evaluation and selection, dimensionality reduction, and sophisticated tuning for finely customized models. "Scikit-Learn Unleashed" is more than just a tutorial; it is a treasure trove of insights, best practices, and actionable examples. It serves as an indispensable resource for data scientists, machine learning engineers, analysts, and anyone committed to unlocking the power of data through machine learning. Begin your journey with Scikit-Learn and empower yourself to solve complex, real-world problems with confidence and expertise.