Mastering Pytorch And Machine Learning
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Mastering Pytorch
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Author : Ashish Ranjan Jha
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-12
Mastering Pytorch written by Ashish Ranjan Jha 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 2021-02-12 with Computers categories.
Master advanced techniques and algorithms for deep learning with PyTorch using real-world examples Key Features Understand how to use PyTorch 1.x to build advanced neural network models Learn to perform a wide range of tasks by implementing deep learning algorithms and techniques Gain expertise in domains such as computer vision, NLP, Deep RL, Explainable AI, and much more Book DescriptionDeep learning is driving the AI revolution, and PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch book will help you uncover expert techniques to get the most out of your data and build complex neural network models. The book starts with a quick overview of PyTorch and explores using convolutional neural network (CNN) architectures for image classification. You'll then work with recurrent neural network (RNN) architectures and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation using generative models and explore the world of generative adversarial networks (GANs). You'll not only build and train your own deep reinforcement learning models in PyTorch but also deploy PyTorch models to production using expert tips and techniques. Finally, you'll get to grips with training large models efficiently in a distributed manner, searching neural architectures effectively with AutoML, and rapidly prototyping models using PyTorch and fast.ai. By the end of this PyTorch book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models.What you will learn Implement text and music generating models using PyTorch Build a deep Q-network (DQN) model in PyTorch Export universal PyTorch models using Open Neural Network Exchange (ONNX) Become well-versed with rapid prototyping using PyTorch with fast.ai Perform neural architecture search effectively using AutoML Easily interpret machine learning (ML) models written in PyTorch using Captum Design ResNets, LSTMs, Transformers, and more using PyTorch Find out how to use PyTorch for distributed training using the torch.distributed API Who this book is for This book is for data scientists, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning paradigms using PyTorch 1.x. Working knowledge of deep learning with Python programming is required.
Mastering Pytorch
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Author : Ashish Ranjan Jha
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-31
Mastering Pytorch written by Ashish Ranjan Jha 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 2024-05-31 with Computers categories.
Master advanced techniques and algorithms for machine learning with PyTorch using real-world examples Updated for PyTorch 2.x, including integration with Hugging Face, mobile deployment, diffusion models, and graph neural networks Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Understand how to use PyTorch to build advanced neural network models Get the best from PyTorch by working with Hugging Face, fastai, PyTorch Lightning, PyTorch Geometric, Flask, and Docker Unlock faster training with multiple GPUs and optimize model deployment using efficient inference frameworks Book DescriptionPyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most out of your data and build complex neural network models. You’ll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation, using generative models, including diffusion models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also learn to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face. By the end of this book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models.What you will learn Implement text, vision, and music generation models using PyTorch Build a deep Q-network (DQN) model in PyTorch Deploy PyTorch models on mobile devices (Android and iOS) Become well versed in rapid prototyping using PyTorch with fastai Perform neural architecture search effectively using AutoML Easily interpret machine learning models using Captum Design ResNets, LSTMs, and graph neural networks (GNNs) Create language and vision transformer models using Hugging Face Who this book is for This deep learning with PyTorch book is for data scientists, machine learning engineers, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python is required.
Mastering Pytorch Second Edition
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Author : Ashish Ranjan Jha
language : en
Publisher:
Release Date : 2024-05-31
Mastering Pytorch Second Edition written by Ashish Ranjan Jha and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.
Master advanced techniques and algorithms for machine learning with PyTorch using real-world examples Updated for PyTorch 2.x, including integration with Hugging Face, mobile deployment, diffusion models, and graph neural networks Purchase of the print or Kindle book includes a free eBook in PDF format Key Features: - Understand how to use PyTorch to build advanced neural network models - Get the best from PyTorch by working with Hugging Face, fastai, PyTorch Lightning, PyTorch Geometric, Flask, and Docker - Unlock faster training with multiple GPUs and optimize model deployment using efficient inference frameworks Book Description: PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most from your data and build complex neural network models. You'll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation using generative models, including diffusion models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also learn to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You'll deploy PyTorch models to production, including mobile devices. Finally, you'll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fastai for prototyping models to training models using PyTorch Lightning. You'll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face. By the end of this book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models. What You Will Learn: - Implement text, vision, and music generating models using PyTorch - Build a deep Q-network (DQN) model in PyTorch - Deploy PyTorch models on mobile devices (Android and iOS) - Become well-versed with rapid prototyping using PyTorch with fast.ai - Perform neural architecture search effectively using AutoML - Easily interpret machine learning models using Captum - Design ResNets, LSTMs, and graph neural networks (GNNs) - Create language and vision transformer models using Hugging Face Who this book is for: This deep learning with PyTorch book is for data scientists, machine learning engineers, machine learning researchers, and deep learning practitioners looking to implement advanced deep learning models using PyTorch. This book is ideal for those looking to switch from TensorFlow to PyTorch. Working knowledge of deep learning with Python is required.
Mastering Pytorch And Machine Learning
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Author : Ed Norex
language : en
Publisher: Independently Published
Release Date : 2024-02-19
Mastering Pytorch And Machine Learning written by Ed Norex and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-19 with Computers categories.
Mastering PyTorch and Machine Learning: Essential Techniques is a comprehensive guide designed to take you on a transformative journey through the world of PyTorch and machine learning. Whether you are a novice eager to dive into the realm of deep learning or an experienced developer aiming to refine your skills, this book serves as your indispensable companion. Dive deep into the fundamentals of PyTorch, exploring its dynamic ecosystem, and unravel the mysteries of tensors, autograd mechanics, and neural network architectures. With detailed discussions on the intricacies of training deep learning models, working with convolutional and recurrent neural networks, and the fascinating world of generative models, this book equips you with the knowledge to tackle modern machine learning challenges. Learn to implement reinforcement learning, manage performance and scalability, and master the art of deploying PyTorch models efficiently. Through practical examples and expert insights, Ed Norex provides the tools and techniques needed to harness the full potential of PyTorch, enabling you to create robust and scalable machine learning models. Mastering PyTorch and Machine Learning: Essential Techniques is more than just a book; it's a gateway to unlocking the future of intelligent applications. Embark on this journey to elevate your skills and become proficient in the art and science of machine learning with PyTorch.
Mastering Deep Learning With Pytorch
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Author : Wilson Hayes
language : en
Publisher: Independently Published
Release Date : 2025-01-02
Mastering Deep Learning With Pytorch written by Wilson Hayes and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-02 with Computers categories.
Ready to dive into the world of artificial intelligence? Mastering Deep Learning with PyTorch: A Practical Guide is the ultimate resource for mastering deep learning using PyTorch, one of the most popular and powerful frameworks for machine learning. Whether you're just starting out or an experienced developer, this book will guide you through the core concepts of deep learning, including building neural networks, working with datasets, and deploying AI models in real-world applications. What You'll Learn: Build Neural Networks: Learn the fundamentals of deep learning and how to implement neural networks in PyTorch. Train AI Models: Gain practical skills in training machine learning models, using optimizers, and fine-tuning performance. Cutting-Edge Techniques: Master advanced topics like CNNs, RNNs, GANs, and reinforcement learning. Efficient Data Handling: Handle large datasets and train models efficiently with distributed computing and mini-batching. Model Deployment: Learn how to deploy your models into production for real-world use cases. What You'll Get: Real-World Applications: From image classification to NLP, this book covers practical projects that reinforce your learning. Hands-On Experience: Apply your knowledge with hands-on examples and projects that you can build and run on your own machine. Advanced Topics: Explore how to apply deep learning to real-world challenges in areas like computer vision, language processing, and AI-driven systems. Why This Book? Comprehensive Approach: We guide you from basic neural network concepts to advanced architectures, all using PyTorch. Perfect for Beginners and Professionals: Whether you're a novice or experienced practitioner, this book offers practical insights and techniques to help you grow. Up-to-Date Information: With the latest updates in PyTorch, you'll have access to cutting-edge tools and methodologies for deep learning. Who Should Read This Book? Beginners eager to learn deep learning and PyTorch. Developers and Data Scientists looking to enhance their skills in machine learning. AI Enthusiasts ready to dive deeper into modern AI applications and techniques. Start Your AI Journey Today! Whether you're aiming to build powerful AI models, explore deep learning concepts, or implement them in real-world applications, Mastering Deep Learning with PyTorch is the practical guide you need to succeed. Get your copy now and start mastering deep learning with PyTorch today!
Machine Learning Mastery Algorithms Applications And Insights
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Author : Dr. Pramod Kumar
language : en
Publisher: Xoffencerpublication
Release Date : 2023-08-14
Machine Learning Mastery Algorithms Applications And Insights written by Dr. Pramod Kumar and has been published by Xoffencerpublication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-14 with Computers categories.
Machine learning is an area of artificial intelligence (AI) that focuses on the development of algorithms and models that allow computers to learn and make predictions or judgments without being explicitly programmed. This is accomplished by teaching the computer to learn from its own experiences. The creation and development of computer systems that are able to automatically analyze and understand complicated data in order to enhance their performance over time is the focus of this field. The foundation of machine learning is the construction of mathematical models that are capable of gaining knowledge from data. These models are educated using a collection of instances that have been labeled. This collection of examples is referred to as the training data, and it includes input features as well as output labels or goal values. Adjusting the model's internal parameters or weights in accordance with the patterns and relationships discovered in the data is what the training process entails. This is done with the intention of achieving a gap that is as narrow as possible between the anticipated outputs and the actual values. Reinforcement learning is a paradigm that entails an agent interacting with an environment and learning to make a series of choices or actions in order to maximize a cumulative reward. This paradigm was developed by Edward de Bono. The agent is provided with feedback in the form of incentives or penalties according to its actions, which teaches it the optimum behavior via the process of trial and error. The methodologies of machine learning are becoming more prevalent in a broad variety of fields and applications. Image and audio recognition, natural language processing, recommendation systems, fraud detection, autonomous cars, and medical diagnostics are just few of the numerous applications that may benefit from AI. Programming languages such as Python and R, in addition to libraries and frameworks such as scikit-learn, TensorFlow, and PyTorch, are often used when it comes to the implementation of machine learning algorithms. These tools offer a comprehensive array of functions and utilities for the preparation of data, as well as for the training, assessment, and deployment of models. Learning via machines is an active topic that is developing at a quick pace because to continuing research and technological breakthroughs. The potential for employing machine learning to tackle difficult issues and promote innovation is continuing to develop as more data becomes accessible and as computer power grows.
Mastering Deep Learning With Pytorch A Practical Guide
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Author : Thompson Carter
language : en
Publisher: Independently Published
Release Date : 2024-10-10
Mastering Deep Learning With Pytorch A Practical Guide written by Thompson Carter and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-10 with Computers categories.
Step into the future of Artificial Intelligence with Mastering Deep Learning with PyTorch: A Practical Guide. Whether you're an AI enthusiast, data scientist, or software engineer, this book delivers a powerful combination of theory and practical, hands-on examples designed to build advanced neural networks with PyTorch. Starting from the fundamentals of deep learning, you'll explore advanced topics like convolutional neural networks (CNNs), recurrent neural networks (RNNs), and transformers. With clear explanations and real-world applications, this guide covers everything from training deep learning models efficiently to deploying them in production environments. Unlock the full potential of PyTorch's dynamic computation graphs and learn to build models that continuously improve. Whether you're working on image recognition, natural language processing, or generative adversarial networks (GANs), this guide equips you with the tools to master deep learning and solve complex AI problems. Don't miss out on the opportunity to elevate your career and transform the way you approach machine learning. Perfect for anyone who wants to stay ahead of the curve in AI development, Mastering Deep Learning with PyTorch offers everything you need to supercharge your AI projects!
Mastering Computer Vision With Pytorch And Machine Learning
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Author : Caide Xiao
language : en
Publisher: Institute of Physics Publishing
Release Date : 2024-04-29
Mastering Computer Vision With Pytorch And Machine Learning written by Caide Xiao and has been published by Institute of Physics Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-29 with Computers categories.
This book is a valuable resource for professionals, researchers, and students who want to expand their knowledge of advanced computer vision techniques using PyTorch.
Learn Pytorch
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Author : Diego Rodrigues
language : en
Publisher: StudioD21
Release Date : 2024-12-10
Learn Pytorch written by Diego Rodrigues and has been published by StudioD21 this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-10 with Business & Economics categories.
This book is ideal for developers and students who want to build deep learning models with PyTorch, combining flexibility, control, and real-world performance. You will learn to apply modern techniques to design, train, and scale robust neural networks in real-world environments, covering everything from fundamentals to advanced architectures. Includes: • Tensor manipulation and Autograd usage • Modular neural network construction with torch.nn • Training with DataLoader, optimizers, and loss functions • Practical application with CNNs, RNNs, Transformers, and GANs • Integration with PyTorch Lightning, TorchScript, and model export • Real-world projects with NLP, computer vision, IoT, and cloud deployment By the end, you will master PyTorch as a professional tool to design scalable AI solutions with technical precision and development agility. pytorch, deep learning, neural networks, torch.nn, autograd, distributed training, cnn, rnn, transformers, deployment
Pytorch Essentials A Comprehensive Guide To Machine Learning Techniques
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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.