Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques

DOWNLOAD
Download Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques 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. If the content not found or just blank you must refresh this page
Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques
DOWNLOAD
Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2024-12-03
Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-03 with Computers categories.
"PyTorch Essentials: A Comprehensive Guide to Machine Learning Techniques" is an essential resource for programmers, researchers, and enthusiasts eager to enhance their mastery of machine learning and artificial intelligence through the PyTorch framework. This guide deftly combines theoretical foundations with hands-on applications, covering everything from basic tensor manipulation and neural network creation to sophisticated architectures such as CNNs, RNNs, and generative models. Additionally, it delves into reinforcement learning, optimization strategies, and best practices for deployment, empowering readers with the skills to develop scalable, production-ready solutions. Whether advancing your research or solving real-world industry challenges, this book serves as your indispensable guide to mastering machine learning with PyTorch.
Machine Learning With Pytorch And Scikit Learn
DOWNLOAD
Author : Sebastian Raschka
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-02-25
Machine Learning With Pytorch And Scikit Learn written by Sebastian Raschka and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-02-25 with Computers categories.
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.
Deep Learning With Pytorch
DOWNLOAD
Author : Luca Pietro Giovanni Antiga
language : en
Publisher: Simon and Schuster
Release Date : 2020-07-01
Deep Learning With Pytorch written by Luca Pietro Giovanni Antiga and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-01 with Computers categories.
“We finally have the definitive treatise on PyTorch! It covers the basics and abstractions in great detail. I hope this book becomes your extended reference document.” —Soumith Chintala, co-creator of PyTorch Key Features Written by PyTorch’s creator and key contributors Develop deep learning models in a familiar Pythonic way Use PyTorch to build an image classifier for cancer detection Diagnose problems with your neural network and improve training with data augmentation Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About The Book Every other day we hear about new ways to put deep learning to good use: improved medical imaging, accurate credit card fraud detection, long range weather forecasting, and more. PyTorch puts these superpowers in your hands. Instantly familiar to anyone who knows Python data tools like NumPy and Scikit-learn, PyTorch simplifies deep learning without sacrificing advanced features. It’s great for building quick models, and it scales smoothly from laptop to enterprise. Deep Learning with PyTorch teaches you to create deep learning and neural network systems with PyTorch. This practical book gets you to work right away building a tumor image classifier from scratch. After covering the basics, you’ll learn best practices for the entire deep learning pipeline, tackling advanced projects as your PyTorch skills become more sophisticated. All code samples are easy to explore in downloadable Jupyter notebooks. What You Will Learn Understanding deep learning data structures such as tensors and neural networks Best practices for the PyTorch Tensor API, loading data in Python, and visualizing results Implementing modules and loss functions Utilizing pretrained models from PyTorch Hub Methods for training networks with limited inputs Sifting through unreliable results to diagnose and fix problems in your neural network Improve your results with augmented data, better model architecture, and fine tuning This Book Is Written For For Python programmers with an interest in machine learning. No experience with PyTorch or other deep learning frameworks is required. About The Authors Eli Stevens has worked in Silicon Valley for the past 15 years as a software engineer, and the past 7 years as Chief Technical Officer of a startup making medical device software. Luca Antiga is co-founder and CEO of an AI engineering company located in Bergamo, Italy, and a regular contributor to PyTorch. Thomas Viehmann is a Machine Learning and PyTorch speciality trainer and consultant based in Munich, Germany and a PyTorch core developer. Table of Contents PART 1 - CORE PYTORCH 1 Introducing deep learning and the PyTorch Library 2 Pretrained networks 3 It starts with a tensor 4 Real-world data representation using tensors 5 The mechanics of learning 6 Using a neural network to fit the data 7 Telling birds from airplanes: Learning from images 8 Using convolutions to generalize PART 2 - LEARNING FROM IMAGES IN THE REAL WORLD: EARLY DETECTION OF LUNG CANCER 9 Using PyTorch to fight cancer 10 Combining data sources into a unified dataset 11 Training a classification model to detect suspected tumors 12 Improving training with metrics and augmentation 13 Using segmentation to find suspected nodules 14 End-to-end nodule analysis, and where to go next PART 3 - DEPLOYMENT 15 Deploying to production
Advanced Deep Learning Techniques For Natural Language Understanding A Comprehensive Guide
DOWNLOAD
Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-09
Advanced Deep Learning Techniques For Natural Language Understanding A Comprehensive Guide written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-09 with Computers categories.
Immerse yourself in the transformative power of deep learning in natural language processing (NLP) with "Advanced Deep Learning Techniques for Natural Language Understanding: A Comprehensive Guide." This all-encompassing volume unravels the complexities of NLP, offering readers a thorough exploration of how cutting-edge deep learning methodologies can be harnessed to comprehend and generate human language with unprecedented precision and efficiency. From the foundational principles of NLP and the underlying mathematical frameworks of deep learning to the practical applications of state-of-the-art models in text classification, machine translation, and more, this guide covers every aspect. Whether you are a novice eager to embark on your NLP journey, a practitioner keen to expand your expertise, or a researcher aspiring to explore the latest advancements, this book delivers the essential knowledge, examples, and insights you require. "Advanced Deep Learning Techniques for Natural Language Understanding: A Comprehensive Guide" is more than a technical manual; it is a gateway to the future of communication, offering a lucid and engaging overview of the most popular deep learning frameworks, the development and deployment of models, and the ethical considerations in NLP. With this guide, you will: - Grasp the core principles and challenges of NLP. - Master the mathematical foundations necessary for creating sophisticated models. - Explore the functionalities of different deep learning frameworks such as TensorFlow, PyTorch, and Keras. - Implement word embeddings and vectorization techniques for text analysis. - Dive into sequence modeling, attention mechanisms, and transformers to refine your NLP models. - Discover practical solutions for real-world applications and the potential of generative models for text. Prepare to embark on a comprehensive journey through the landscape of NLP, equipped with the tools and knowledge to leverage the power of deep learning. "Advanced Deep Learning Techniques for Natural Language Understanding: A Comprehensive Guide" is your essential resource for unlocking the potential of language, transforming how machines understand us and how we interact with the digital world.
Machine Learning Essentials
DOWNLOAD
Author : Barrett Williams
language : en
Publisher: Barrett Williams
Release Date : 2024-12-01
Machine Learning Essentials written by Barrett Williams and has been published by Barrett Williams this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-01 with Computers categories.
Unlock the potential of data and step into the future with "Machine Learning Essentials," the ultimate guide for mastering predictive analytics. Whether you're a newcomer or looking to deepen your understanding, this comprehensive eBook is designed to equip you with the tools and knowledge you need to excel in the dynamic field of machine learning. Begin your journey by exploring the foundational principles of machine learning and its transformative impact on predictive analytics. Learn how to expertly prepare and engineer your data, selecting and extracting the features that matter most. Dive into handling imbalanced data with precision, ensuring your models are accurate and robust. Discover the power of classification algorithms with insights into decision trees, random forests, support vector machines, and logistic regression. Transition smoothly into regression techniques, harnessing the potential of linear, polynomial, and regularization methods. Explore the realm of unsupervised learning to unveil predictive insights using clustering methods, dimensionality reduction techniques, and anomaly detection. Evaluate model performance like a pro with cross-validation strategies, confusion matrices, and ROC/AUC metrics. Venture into neural networks, unlocking the basics of their architecture, activation functions, and training methodologies. Delve into advanced deep learning topics with convolutional, recurrent, and generative adversarial networks. Optimize your models through hyperparameter tuning and feature importance analysis, selecting the most effective techniques for your goals. Gain practical business insights by implementing machine learning in marketing analytics, risk assessment, and fraud detection. Familiarize yourself with essential tools and libraries like Python, Scikit-Learn, TensorFlow, and PyTorch. Learn from real-world case studies in retail, healthcare, and finance, and tackle ethical considerations in algorithmic bias and data security. Prepare for the future with insights into automated machine learning, IoT, and evolving AI technologies. Take practical steps to launch your machine learning journey, setting up your environment and connecting with a vibrant community of practitioners. "Machine Learning Essentials" is your all-in-one resource for gaining actionable expertise and driving innovation in today's data-driven world. Start your learning adventure today and transform your career with this indispensable guide.
Deep Learning For Coders With Fastai And Pytorch
DOWNLOAD
Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard and has been published by O'Reilly Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Mastering Machine Learning A Comprehensive Guide To Success
DOWNLOAD
Author : Rick Spair
language : en
Publisher: Rick Spair
Release Date : 2023-06-14
Mastering Machine Learning A Comprehensive Guide To Success written by Rick Spair and has been published by Rick Spair this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-14 with Computers categories.
Welcome to "Mastering Machine Learning: A Comprehensive Guide to Success." In this book, we embark on an exciting journey into the world of machine learning (ML), exploring its concepts, techniques, and practical applications. Whether you are a beginner taking your first steps into the field or an experienced practitioner seeking to deepen your knowledge, this comprehensive guide will equip you with the tools, strategies, and insights needed to succeed in the ever-evolving landscape of ML. Machine learning is a rapidly advancing field that has revolutionized industries and transformed the way we tackle complex problems. From personalized recommendations and speech recognition systems to autonomous vehicles and medical diagnostics, machine learning has become an integral part of our daily lives. Its ability to analyze vast amounts of data, identify patterns, and make predictions has paved the way for groundbreaking advancements across various domains. However, mastering machine learning requires more than just understanding the algorithms and techniques. It requires a holistic approach that encompasses data collection and preparation, exploratory data analysis, model building, evaluation, deployment, and continuous learning. It also demands a deep understanding of the ethical and social implications of machine learning, ensuring responsible and fair use of this powerful technology. In this book, we have carefully crafted 20 comprehensive chapters that cover a wide range of topics, from the fundamentals of machine learning to advanced techniques and future trends. Each chapter provides a deep dive into a specific aspect of machine learning, offering tips, recommendations, and strategies for success. You will learn about various algorithms, data preprocessing techniques, model evaluation methods, interpretability approaches, and much more. Throughout the book, we emphasize a practical approach to machine learning. Real-world examples, case studies, and hands-on exercises are incorporated to help you gain a deeper understanding of the concepts and apply them to your own projects. We believe that active learning and practical experience are crucial for mastering machine learning, and we encourage you to explore, experiment, and build your own models. While this book serves as a comprehensive guide, it is important to note that machine learning is a rapidly evolving field. New algorithms, techniques, and technologies are constantly emerging, and staying up-to-date with the latest advancements is essential. However, the principles and foundations discussed in this book will provide you with a solid framework to adapt and navigate the ever-changing landscape of machine learning. Whether you are an aspiring data scientist, a software engineer, a researcher, or a business professional, this book is designed to be your trusted companion in your journey to mastering machine learning. By the time you reach the end, you will have gained a deep understanding of the fundamental concepts, acquired practical skills for applying machine learning in real-world scenarios, and developed the mindset needed to tackle complex challenges and drive innovation. Get ready to embark on an exciting adventure into the world of machine learning. Let's begin our journey towards mastering machine learning and unlocking its full potential. Happy learning!
Machine Learning Exam Essentials
DOWNLOAD
Author : cybellim
language : en
Publisher: Cybellium Ltd
Release Date : 2024-10-26
Machine Learning Exam Essentials written by cybellim and has been published by Cybellium Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-26 with Study Aids categories.
Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Mastering Data Science A Comprehensive Guide To Techniques And Applications
DOWNLOAD
Author : Adam Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-05
Mastering Data Science A Comprehensive Guide To Techniques And Applications written by Adam Jones and has been published by Walzone Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-05 with Computers categories.
Embark on your data science journey with "Mastering Data Science: A Comprehensive Guide to Techniques and Applications," the ultimate resource for mastering the vast landscape of data science. Whether you're a novice eager to explore the field or an expert looking to refine and expand your skills, this book provides a thorough exploration of essential data science techniques and applications. Discover the foundational principles of data wrangling, preprocessing, statistical fundamentals, and essential mathematical techniques. Delve into the complexities of machine learning, deep learning, and natural language processing with clear explanations that connect theory to real-world practice. Each chapter is carefully designed to unravel complex concepts and features practical examples to enhance your understanding. Explore the intricacies of time series analysis, develop proficiency in crafting compelling data visualizations, and learn to effectively deploy machine learning models. With a focus on practical application, this guide not only imparts theoretical insights but also empowers you to address data science challenges confidently. Unlock the potential of data science to innovate, solve critical problems, and make informed decisions in today's data-centric world with "Mastering Data Science: A Comprehensive Guide to Techniques and Applications."
Pytorch Cookbook
DOWNLOAD
Author : Matthew Rosch
language : en
Publisher: GitforGits
Release Date : 2023-10-04
Pytorch Cookbook written by Matthew Rosch and has been published by GitforGits this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-10-04 with Computers categories.
Starting a PyTorch Developer and Deep Learning Engineer career? Check out this 'PyTorch Cookbook,' a comprehensive guide with essential recipes and solutions for PyTorch and the ecosystem. The book covers PyTorch deep learning development from beginner to expert in well-written chapters. The book simplifies neural networks, training, optimization, and deployment strategies chapter by chapter. The first part covers PyTorch basics, data preprocessing, tokenization, and vocabulary. Next, it builds CNN, RNN, Attentional Layers, and Graph Neural Networks. The book emphasizes distributed training, scalability, and multi-GPU training for real-world scenarios. Practical embedded systems, mobile development, and model compression solutions illuminate on-device AI applications. However, the book goes beyond code and algorithms. It also offers hands-on troubleshooting and debugging for end-to-end deep learning development. 'PyTorch Cookbook' covers data collection to deployment errors and provides detailed solutions to overcome them. This book integrates PyTorch with ONNX Runtime, PySyft, Pyro, Deep Graph Library (DGL), Fastai, and Ignite, showing you how to use them for your projects. This book covers real-time inferencing, cluster training, model serving, and cross-platform compatibility. You'll learn to code deep learning architectures, work with neural networks, and manage deep learning development stages. 'PyTorch Cookbook' is a complete manual that will help you become a confident PyTorch developer and a smart Deep Learning engineer. Its clear examples and practical advice make it a must-read for anyone looking to use PyTorch and advance in deep learning. Key Learnings Comprehensive introduction to PyTorch, equipping readers with foundational skills for deep learning. Practical demonstrations of various neural networks, enhancing understanding through hands-on practice. Exploration of Graph Neural Networks (GNN), opening doors to cutting-edge research fields. In-depth insight into PyTorch tools and libraries, expanding capabilities beyond core functions. Step-by-step guidance on distributed training, enabling scalable deep learning and AI projects. Real-world application insights, bridging the gap between theoretical knowledge and practical execution. Focus on mobile and embedded development with PyTorch, leading to on-device AI. Emphasis on error handling and troubleshooting, preparing readers for real-world challenges. Advanced topics like real-time inferencing and model compression, providing future ready skill. Table of Content Introduction to PyTorch 2.0 Deep Learning Building Blocks Convolutional Neural Networks Recurrent Neural Networks Natural Language Processing Graph Neural Networks (GNNs) Working with Popular PyTorch Tools Distributed Training and Scalability Mobile and Embedded Development