Practical Machine Learning With Scikit Learn And Pytorch
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Machine Learning With Pytorch And Scikit Learn
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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.
Practical Machine Learning With Scikit Learn And Pytorch
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Author : Cody Coker
language : en
Publisher: Independently Published
Release Date : 2025-11-02
Practical Machine Learning With Scikit Learn And Pytorch written by Cody Coker and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-11-02 with Computers categories.
✨ Your Journey into Machine Learning Starts Here! Book Description: Practical Machine Learning with Scikit-Learn and PyTorch Feeling overwhelmed by machine learning buzzwords and complex math? You're not alone!
Hands On Machine Learning With Scikit Learn And Pytorch
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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-10-22
Hands On Machine Learning With Scikit Learn And Pytorch written by Aurélien Géron and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-22 with Computers categories.
The potential of machine learning today is extraordinary, yet many aspiring developers and tech professionals find themselves daunted by its complexity. 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. With an approachable yet deeply informative style, author Aurélien Géron delivers the ultimate introductory guide to machine learning and deep learning. Drawing on the Hugging Face ecosystem, with a focus on clear explanations and real-world examples, the book takes you through cutting-edge tools like Scikit-Learn and PyTorch—from basic regression techniques to advanced neural networks. Whether you're a student, professional, or hobbyist, you'll gain the skills to build intelligent systems. Understand ML basics, including concepts like overfitting and hyperparameter tuning Complete an end-to-end ML project using scikit-Learn, covering everything from data exploration to model evaluation Learn techniques for unsupervised learning, such as clustering and anomaly detection Build advanced architectures like transformers and diffusion models with PyTorch Harness the power of pretrained models—including LLMs—and learn to fine-tune them Train autonomous agents using reinforcement learning
Python Machine Learning By Example
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Author : Yuxi (Hayden) Liu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-10-30
Python Machine Learning By Example written by Yuxi (Hayden) Liu 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 2020-10-30 with Computers categories.
A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniques Key FeaturesDive into machine learning algorithms to solve the complex challenges faced by data scientists todayExplore cutting edge content reflecting deep learning and reinforcement learning developmentsUse updated Python libraries such as TensorFlow, PyTorch, and scikit-learn to track machine learning projects end-to-endBook Description Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naïve Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting with sequences using recurring neural networks, and leveraging reinforcement learning for making decisions, the book has been considerably updated for the latest enterprise requirements. At the same time, this book provides actionable insights on the key fundamentals of ML with Python programming. Hayden applies his expertise to demonstrate implementations of algorithms in Python, both from scratch and with libraries. Each chapter walks through an industry-adopted application. With the help of realistic examples, you will gain an understanding of the mechanics of ML techniques in areas such as exploratory data analysis, feature engineering, classification, regression, clustering, and NLP. By the end of this ML Python book, you will have gained a broad picture of the ML ecosystem and will be well-versed in the best practices of applying ML techniques to solve problems. What you will learnUnderstand the important concepts in ML and data scienceUse Python to explore the world of data mining and analyticsScale up model training using varied data complexities with Apache SparkDelve deep into text analysis and NLP using Python libraries such NLTK and GensimSelect and build an ML model and evaluate and optimize its performanceImplement ML algorithms from scratch in Python, TensorFlow 2, PyTorch, and scikit-learnWho this book is for If you’re a machine learning enthusiast, data analyst, or data engineer highly passionate about machine learning and want to begin working on machine learning assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial, although this is not necessary.
Mastering Machine Learning With Scikit Learn And Pytorch
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Author : BRYAN L. CHANG
language : en
Publisher: Independently Published
Release Date : 2025-09-23
Mastering Machine Learning With Scikit Learn And Pytorch written by BRYAN L. CHANG and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-23 with Computers categories.
Have you ever wanted to truly understand machine learning, not just superficially, but in a way that allows you to build, experiment, and master intelligent systems from scratch? Are you tired of jumping between tutorials, struggling with scattered resources, and never getting a complete picture of how modern machine learning really works? Mastering Machine Learning with Scikit-Learn and PyTorch is designed to be your comprehensive guide. Whether you're a beginner looking to grasp the fundamentals or a professional aiming to sharpen your skills, this book walks you through every step of creating powerful, real-world machine learning systems. Have you wondered how to prepare and transform raw data into insights? Or how to choose the right model, optimize its performance, and validate it for accuracy? This book covers all of that in depth. From classic predictive models to advanced neural networks, you will learn how to design, implement, and troubleshoot algorithms effectively. Do you want to explore deep learning without being overwhelmed by complexity? This book takes you through neural networks, convolutional networks for image processing, recurrent models for sequences, and even the cutting-edge concepts of attention mechanisms. Each concept is explained clearly, with practical, hands-on examples so you can implement them using approachable tools for learning and experimentation. Are you looking for guidance on scaling your models, deploying them, and integrating them into real applications? This book goes beyond theory to show how machine learning can be applied to real-world problems, from data preprocessing to model deployment, and even responsible AI practices for ethical decision-making. By the end of this book, you won't just know machine learning-you will understand it, master it, and be ready to apply it. You'll gain confidence in both structured algorithms and flexible deep learning frameworks, giving you the skills to tackle any data-driven challenge. If you've ever wanted a single, reliable resource that turns confusion into clarity, theory into practice, and data into intelligence, this book is for you. Get ready to transform your understanding of machine learning and start building intelligent systems with confidence.
Hands On Machine Learning With Python
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Author : Ashwin Pajankar
language : en
Publisher: Apress
Release Date : 2022-03-20
Hands On Machine Learning With Python written by Ashwin Pajankar and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-20 with Computers categories.
Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios. The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoretical and practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch. After completing Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage. What You'll Learn Review data structures in NumPy and Pandas Demonstrate machine learning techniques and algorithm Understand supervised learning and unsupervised learning Examine convolutional neural networks and Recurrent neural networks Get acquainted with scikit-learn and PyTorch Predict sequences in recurrent neural networks and long short term memory Who This Book Is For Data scientists, machine learning engineers, and software professionals with basic skills in Python programming.
Python Machine Learning
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Author : Oscar Elliot
language : en
Publisher: Oscar Elliot
Release Date : 2021-03-30
Python Machine Learning written by Oscar Elliot and has been published by Oscar Elliot this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-30 with categories.
The world of machine learning is changing all the time. It is so amazing the idea that we are able to take a computer and let it learn as it goes. Without having to write out all of the codes that we need for every situation out there or every input that the user may pick, we are able to write out codes in machine learning, even with Python, in order to let the computer or device learn and make decisions on its own. This guidebook is going to take a closer look at how Python machine learning is able to work, as well as how you can use some of the tools and techniques that come with this process for your own needs. When you are interested in learning more about what machine learning is all about, as well as how you can use a part of the coding from Python inside of this process, then this guidebook is the tool for you! Some of the topics that we will explore when we go through this guidebook will include: - Understanding some of the basics of machine learning; - Some of the different parts that you need to know to get started with machine learning and the Python language; - Understanding the Scikit-Learn library, and why it is so important to work with this type of library; - How to work with the K-Nearest Neighbors algorithm; - What are support vector machines, random forest algorithm, and recurrent neural networks; - What are linear classifiers; - How K-Means clustering is going to be different from KNN; - Other great things that you are able to do with Python Machine Learning. The field of machine learning is growing exponentially-and with the help of Python and all of the cool tools and libraries that come with it, you will find that there are endless possibilities of what you will be able to do with it. When you are ready to learn more about Python Machine Learning and when you want to be able to work towards your own projects and applications with this cool topic, make sure to check out this guidebook to help you get started! Scroll to the top of the page and select the buy now button!
Mastering Machine Learning With Tensorflow Pytorch And Scikit Learn
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Author : Dr Benjamin Neudorf
language : en
Publisher: Independently Published
Release Date : 2025-08-27
Mastering Machine Learning With Tensorflow Pytorch And Scikit Learn written by Dr Benjamin Neudorf and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-27 with Computers categories.
Unlock the Power of Machine Learning-No Experience Required Are you fascinated by artificial intelligence but feel overwhelmed by the jargon, complexity, or sheer scale of machine learning? Do you dream of building intelligent systems, but worry you lack the background, confidence, or mathematical skills to get started? You're not alone-and this book is for you. Mastering Machine Learning with TensorFlow, PyTorch, and Scikit-Learn: A Practical Python Guide is your friendly, step-by-step introduction to modern machine learning. Whether you're a complete beginner or a curious developer, you'll discover how easy-and fun-machine learning can be with the right guide at your side. What You'll Find Inside: Beginner-Friendly Approach: No prior experience in machine learning, statistics, or advanced Python required. Every concept is broken down into plain language and hands-on examples, guiding you gently from your very first line of code to complete, working projects. Confidence-Building Tutorials: Learn by doing with real-world datasets, detailed walkthroughs, and plenty of practical exercises-so you'll never feel lost or left behind. Three Powerful Frameworks, One Book: Master the essentials of TensorFlow, PyTorch, and Scikit-Learn-the leading Python libraries used by top companies and research labs worldwide. Real-World Projects: Go beyond theory. Build your own machine learning models for regression, classification, image recognition, and more, using code you can run, adapt, and expand for your own ideas. Supportive, Encouraging Voice: Mistakes are normal-and often the best teachers. Throughout this book, you'll find troubleshooting tips, gentle encouragement, and guidance that celebrates your progress and every small win. Key Benefits: Gain a clear, practical understanding of the entire machine learning workflow-from data preparation to model deployment. Develop strong Python skills while building confidence with professional tools and libraries. Understand core concepts like neural networks, deep learning, transfer learning, and explainable AI without the intimidation. Apply your new skills immediately to real problems, unlocking doors in tech, business, research, and beyond. Why This Book Stands Out: Step-by-step, project-based lessons perfect for absolute beginners. Friendly explanations that demystify machine learning and artificial intelligence. Practical, working code for every topic-no more guesswork or copying from unreliable sources. Written by an experienced educator who remembers what it feels like to start from scratch. Ready to Begin Your Machine Learning Journey? You don't need a PhD or years of experience. All you need is curiosity, determination, and the right companion to guide you. Start reading Mastering Machine Learning with TensorFlow, PyTorch, and Scikit-Learn today-and take your first confident step toward a future in AI. Don't just learn machine learning-master it, one step at a time. Scroll up and get your copy now!
Deep Learning With Pytorch
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Author : Vishnu Subramanian
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-02-23
Deep Learning With Pytorch written by Vishnu Subramanian 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 2018-02-23 with Computers categories.
Build neural network models in text, vision and advanced analytics using PyTorch Key Features Learn PyTorch for implementing cutting-edge deep learning algorithms. Train your neural networks for higher speed and flexibility and learn how to implement them in various scenarios; Cover various advanced neural network architecture such as ResNet, Inception, DenseNet and more with practical examples; Book Description Deep learning powers the most intelligent systems in the world, such as Google Voice, Siri, and Alexa. Advancements in powerful hardware, such as GPUs, software frameworks such as PyTorch, Keras, Tensorflow, and CNTK along with the availability of big data have made it easier to implement solutions to problems in the areas of text, vision, and advanced analytics. This book will get you up and running with one of the most cutting-edge deep learning libraries—PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its accessibility, efficiency and being more native to Python way of development. You'll start off by installing PyTorch, then quickly move on to learn various fundamental blocks that power modern deep learning. You will also learn how to use CNN, RNN, LSTM and other networks to solve real-world problems. This book explains the concepts of various state-of-the-art deep learning architectures, such as ResNet, DenseNet, Inception, and Seq2Seq, without diving deep into the math behind them. You will also learn about GPU computing during the course of the book. You will see how to train a model with PyTorch and dive into complex neural networks such as generative networks for producing text and images. By the end of the book, you'll be able to implement deep learning applications in PyTorch with ease. What you will learn Use PyTorch for GPU-accelerated tensor computations Build custom datasets and data loaders for images and test the models using torchvision and torchtext Build an image classifier by implementing CNN architectures using PyTorch Build systems that do text classification and language modeling using RNN, LSTM, and GRU Learn advanced CNN architectures such as ResNet, Inception, Densenet, and learn how to use them for transfer learning Learn how to mix multiple models for a powerful ensemble model Generate new images using GAN’s and generate artistic images using style transfer Who this book is for This book is for machine learning engineers, data analysts, data scientists interested in deep learning and are looking to explore implementing advanced algorithms in PyTorch. Some knowledge of machine learning is helpful but not a mandatory need. Working knowledge of Python programming is expected.
Deep Learning And Machine Learning For Beginners
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Author : Dr Adrian Devlin
language : en
Publisher: Independently Published
Release Date : 2025-10-17
Deep Learning And Machine Learning For Beginners written by Dr Adrian Devlin and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-17 with Computers categories.
Are you curious about artificial intelligence and machine learning, but worried you're not "technical" enough to start? You're not alone-and this book was written especially for you. Deep Learning and Machine Learning for Beginners is your supportive, step-by-step guide to mastering the modern world of AI-no advanced math, coding experience, or background required. Whether you've felt lost in jargon, overwhelmed by complex code, or simply unsure where to begin, this friendly book will show you the way with patience, warmth, and encouragement. Why This Book? Start from Scratch: You'll learn everything you need, from Python basics to building your first real machine learning models, all explained in plain English. Hands-On and Practical: Tackle real-world projects with PyTorch, TensorFlow, and Scikit-Learn. You won't just read about data science and neural networks-you'll actually build them, one small step at a time. Mistakes Welcome: Learning technology can be intimidating. This book normalizes trial and error, celebrating each small win and helping you turn confusion into confidence. Accessible Explanations: Every chapter is crafted with complete beginners in mind. Technical concepts are broken down into simple, relatable ideas-making advanced topics like deep learning approachable for everyone. Supportive Tone: The author shares personal insights, encouragement, and practical tips to help you enjoy the journey, avoid frustration, and stay motivated. What You'll Learn: The core ideas behind machine learning and deep learning, demystified How to prepare, clean, and understand data for real-world projects Building and evaluating models using Scikit-Learn, PyTorch, and TensorFlow Creating practical applications-from image recognition to text classification and more Key tools, workflows, and coding best practices to set you up for success How to overcome self-doubt and celebrate progress at every step Perfect For: Complete beginners and self-learners eager to break into artificial intelligence and data science Students, career-changers, and anyone ready to build valuable new tech skills Readers seeking a kind, confidence-building companion on their coding journey If you're ready to stop feeling intimidated by technology and start building real AI projects with confidence, this is the book for you. With every chapter, you'll discover that machine learning isn't just for "experts"-it's for anyone willing to learn, experiment, and grow. Start your empowering journey today-discover the exciting world of deep learning and machine learning, one step at a time!