Machine Learning With Scikit Learn And Tensorflow
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Hands On Machine Learning With Scikit Learn Keras And Tensorflow
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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-09-05
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 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 2019-09-05 with Computers categories.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You’ll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you’ve learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets
Hands On Machine Learning With Scikit Learn Keras And Tensorflow
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Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-10-04
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 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 2022-10-04 with Computers categories.
Through a recent series of breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This bestselling book uses concrete examples, minimal theory, and production-ready Python frameworks (Scikit-Learn, Keras, and TensorFlow) to help you gain an intuitive understanding of the concepts and tools for building intelligent systems. With this updated third edition, author Aurélien Géron explores a range of techniques, starting with simple linear regression and progressing to deep neural networks. Numerous code examples and exercises throughout the book help you apply what you've learned. Programming experience is all you need to get started. Use Scikit-learn to track an example ML project end to end Explore several models, including support vector machines, decision trees, random forests, and ensemble methods Exploit unsupervised learning techniques such as dimensionality reduction, clustering, and anomaly detection Dive into neural net architectures, including convolutional nets, recurrent nets, generative adversarial networks, autoencoders, diffusion models, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning
Tensorflow Machine Learning
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Author : Benjamin Smith
language : en
Publisher:
Release Date : 2021-01-04
Tensorflow Machine Learning written by Benjamin Smith and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-04 with categories.
Have you ever wondered how machine learning works? These days, machine learning, deep learning and neural nets are common terms and they are here to stay as a part of our everyday language. Machine learning is not the easiest of topics to teach, purely because there is so much to it. Machine learning, deep learning and artificial intelligence are used in more applications than most humans even think about - email, Amazon, Netflix, Spotify, and other popular online marketplaces use machine learning to weed out spam emails and bring you recommendations based on your shopping or streaming preferences. Machine learning is used in healthcare, in finance, in just about every industry you can think of - it's here to stay, whether we like it or not.One of the most important parts of learning machine learning is knowing which algorithm to choose and which library. Python is the most popular machine learning programming language and it has a huge advantage over other languages - the large amount of built-in libraries; three of the most important are TensorFlow, Keras and Scikit-Learn. And that's what this book is about - machine learning with TensorFlow, Keras and Scikit-learn. Here's what you will learn: -What machine learning is-How it applies in the real world-Different models and learning types-Different machine learning algorithms-Deep learning vs. machine learning-What TensorFlow is and how to use it-What TensorFlow comprises-Operators, variables, placeholders, and more-What Keras is and how to use it-Keras vs. TensorFlow-How to use Keras for linear regression-How to use Keras to build a neural net-What Scikit-Learn is and how to use it-Using Scikit-Learn to build regression and classification trees-How to build a random forest model-How to install Keras, TensorFlow and Scikit-LearnAnd much more!All the practical examples in the book use Python, so you are expected to need some knowledge of the language before you start. If you're looking to advanced your skills in machine learning, then this is the book for you! Grab your copy of this book today!
Hands On Machine Learning With Scikit Learn And Tensorflow
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Author : Aurélien Géron
language : en
Publisher:
Release Date : 2017
Hands On Machine Learning With Scikit Learn And Tensorflow written by Aurélien Géron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Machine Learning With Scikit Learn And Tensorflow Deep Learning With Python Random Forests Decision Trees And Neural Networks
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Author : Emery H. Maxwell
language : en
Publisher: Independently Published
Release Date : 2019-03-29
Machine Learning With Scikit Learn And Tensorflow Deep Learning With Python Random Forests Decision Trees And Neural Networks written by Emery H. Maxwell and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-03-29 with Computers categories.
It appears that the development of artificial intelligence is expanding. Certain tools are working behind the scenes of everyday life as prediction models by allowing computers to learn and act without human intervention.The result so far has been self-driving vehicles, improved internet browsing, and more.Even if you are not a programmer or data scientist, it can still be interesting to discover how machine learning works.This book is intended to guide you through the fundamentals of machine learning through Python, Scikit-Learn, and TensorFlow.It will cover: - An overview of Python, neural networks, Scikit-Learn, TensorFlow, random forests, decision trees, machine learning, and deep learning- How to get started with Python- How to run a line of code- How to get started with Scikit-Learn- How to work with data- How to use TensorFlow- How to use datasets- Computational graphs- How search algorithms work- How clustering algorithms work- . . . and more
Python Machine Learning
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Author : Sebastian Raschka
language : en
Publisher: Packt Publishing Ltd
Release Date : 2019-12-12
Python Machine Learning 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 2019-12-12 with Computers categories.
Applied machine learning with a solid foundation in theory. Revised and expanded for TensorFlow 2, GANs, and reinforcement learning. Purchase of the print or Kindle book includes a free eBook in the PDF format. Key Features Third edition of the bestselling, widely acclaimed Python machine learning book Clear and intuitive explanations take you deep into the theory and practice of Python machine learning Fully updated and expanded to cover TensorFlow 2, Generative Adversarial Network models, reinforcement learning, and best practices Book Description Python Machine Learning, Third Edition is a comprehensive guide to machine learning and deep learning with Python. 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 working 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, Raschka and Mirjalili teach the principles behind machine learning, allowing you to build models and applications for yourself. Updated for TensorFlow 2.0, this new third edition introduces readers to its new Keras API features, as well as the latest additions to scikit-learn. It's also expanded to cover cutting-edge reinforcement learning techniques based on deep learning, as well as an introduction to GANs. Finally, this book also explores a subfield of natural language processing (NLP) called sentiment analysis, helping you learn how to use machine learning algorithms to classify documents. This 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 Master the frameworks, models, and techniques that enable machines to 'learn' from data Use scikit-learn for machine learning and TensorFlow for deep learning Apply machine learning to image classification, sentiment analysis, intelligent web applications, and more Build and train neural networks, GANs, and other models 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 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. Written for developers and data scientists who want to create practical machine learning and deep learning code, this book is ideal for anyone who wants to teach computers how to learn from data.
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 2nd Edition
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Author : Aurélien Géron
language : en
Publisher:
Release Date : 2019
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 2nd Edition written by Aurélien Géron and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with categories.
Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how. By using concrete examples, minimal theory, and two production-ready Python frameworks-Scikit-Learn and TensorFlow-author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started. Explore the machine learning landscape, particularly neural nets Use Scikit-Learn to track an example machine-learning project end-to-end Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods Use the TensorFlow library to build and train neural nets Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets.
Tensorflow Machine Learning
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Author : Benjamin Smith
language : en
Publisher: Independently Published
Release Date : 2020-08-24
Tensorflow Machine Learning written by Benjamin Smith and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-24 with categories.
Machine Learning is an emerging field in the discipline of computer science. The possibilities are virtually endless and the things we can achieve with machine learning bridge the gap between reality and science fiction. If you are one of those people who developed an interest and learned the basics of machine learning and want to improve your foundation, then this is the right book for you. Here's a list of some of the distinct features of this book that set it apart from others: -This book includes a comprehensive and detailed explanation of the concepts. No chapter has idle talk. Every line in this book has been written while keeping the convenience and interest of the reader in mind.-This book features some really cool tips and tricks that build upon some very basic and fundamental practices of machine learning. Using these tips and tricks will help increase the productivity of your models.-Each topic addresses some of the most important issues that users experience when working with machine learning. For instance, in the later parts of this book, after discussing deep learning, we shift our focus towards the main challenges that arise when creating and implementing a complex and large deep neural network.-This book aims to give readers a productive reading session. In order to accomplish this, each chapter has fragmented sections that highlight interesting topics. Furthermore, the chapter layout guides the reader through the many concepts of machine learning very easily.If you're interested in tips and tricks to machine learning with the use of scikit-learn, keras and Tensorflow, then click the BUY NOW button to get started today!
Machine Learning With Scikit Learn And Tensorflow
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Author : David T Powell
language : en
Publisher: Independently Published
Release Date : 2025-12-07
Machine Learning With Scikit Learn And Tensorflow written by David T Powell and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-12-07 with Computers categories.
Machine Learning with Scikit-Learn and TensorFlow: A Hands-On Guide to Scikit-Learn and TensorFlow for Real World AI This book is the definitive, hands-on guide for developers and data scientists looking to master the end-to-end Machine Learning pipeline. Starting with the foundational principles of data representation, statistics, and optimization (calculus, gradient descent), the book provides a comprehensive journey across the entire ML landscape. Part I focuses on classical methods using Scikit-Learn, covering linear models, evaluation metrics (ROC, AUC, F1-Score), Support Vector Machines, and powerful ensemble techniques like Random Forests and Gradient Boosting. Part II shifts entirely to Deep Learning with TensorFlow and Keras, tackling the instability of deep networks (vanishing/exploding gradients) using modern solutions like Batch Normalization and Transfer Learning. Readers will learn to architect specialized networks, including Convolutional Neural Networks (CNNs) for vision, Recurrent Neural Networks (RNNs) for sequence processing, and Generative Adversarial Networks (GANs) for creating new data. The final section addresses production readiness, detailing scalable data pipelines (tf.data), distributed training strategies, and deployment using the SavedModel format, TensorFlow Serving, and TensorFlow Lite for edge devices. This guide ensures practitioners can not only build sophisticated models but also deploy and monitor them reliably at scale.
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.