Hands On Machine Learning With Scikit Learn Keras Tensorflow
DOWNLOAD eBooks
Download Hands On Machine Learning With Scikit Learn Keras Tensorflow PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Hands On Machine Learning With Scikit Learn Keras Tensorflow 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
Hands On Machine Learning With Scikit Learn Keras And Tensorflow
DOWNLOAD eBooks
Author : Aurélien Géron
language : en
Publisher: O'Reilly Media
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 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
DOWNLOAD eBooks
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
DOWNLOAD eBooks
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
Hands On Machine Learning With Scikit Learn And Tensorflow
DOWNLOAD eBooks
Author : Aurélien Géron
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2017-03-13
Hands On Machine Learning With Scikit Learn 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 2017-03-13 with Computers categories.
Graphics in this book are printed in black and white. 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 Apply practical code examples without acquiring excessive machine learning theory or algorithm details
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 3rd Edition
DOWNLOAD eBooks
Author : Aurélien Géron
language : en
Publisher:
Release Date : 2022
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 3rd 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 2022 with 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 best-selling 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 Aurelien Geron 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 machine learning 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, and transformers Use TensorFlow and Keras to build and train neural nets for computer vision, natural language processing, generative models, and deep reinforcement learning Train neural nets using multiple GPUs and deploy them at scale using Google's Vertex AI.
Mathematics For Machine Learning
DOWNLOAD eBooks
Author : Marc Peter Deisenroth
language : en
Publisher: Cambridge University Press
Release Date : 2020-04-23
Mathematics For Machine Learning written by Marc Peter Deisenroth and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-23 with Computers categories.
Distills key concepts from linear algebra, geometry, matrices, calculus, optimization, probability and statistics that are used in machine learning.
Machine Learning
DOWNLOAD eBooks
Author : Stephen Marsland
language : en
Publisher: CRC Press
Release Date : 2011-03-23
Machine Learning written by Stephen Marsland and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-03-23 with Business & Economics categories.
Traditional books on machine learning can be divided into two groups- those aimed at advanced undergraduates or early postgraduates with reasonable mathematical knowledge and those that are primers on how to code algorithms. The field is ready for a text that not only demonstrates how to use the algorithms that make up machine learning methods, but
Hands On Machine Learning With Scikit Learn Keras And Tensorflow 2nd Edition
DOWNLOAD eBooks
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.
Hands On Gradient Boosting With Xgboost And Scikit Learn
DOWNLOAD eBooks
Author : Corey Wade
language : en
Publisher: Packt Publishing Ltd
Release Date : 2020-10-16
Hands On Gradient Boosting With Xgboost And Scikit Learn written by Corey Wade 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 2020-10-16 with Computers categories.
Get to grips with building robust XGBoost models using Python and scikit-learn for deployment Key Features Get up and running with machine learning and understand how to boost models with XGBoost in no time Build real-world machine learning pipelines and fine-tune hyperparameters to achieve optimal results Discover tips and tricks and gain innovative insights from XGBoost Kaggle winners Book Description XGBoost is an industry-proven, open-source software library that provides a gradient boosting framework for scaling billions of data points quickly and efficiently. The book introduces machine learning and XGBoost in scikit-learn before building up to the theory behind gradient boosting. You'll cover decision trees and analyze bagging in the machine learning context, learning hyperparameters that extend to XGBoost along the way. You'll build gradient boosting models from scratch and extend gradient boosting to big data while recognizing speed limitations using timers. Details in XGBoost are explored with a focus on speed enhancements and deriving parameters mathematically. With the help of detailed case studies, you'll practice building and fine-tuning XGBoost classifiers and regressors using scikit-learn and the original Python API. You'll leverage XGBoost hyperparameters to improve scores, correct missing values, scale imbalanced datasets, and fine-tune alternative base learners. Finally, you'll apply advanced XGBoost techniques like building non-correlated ensembles, stacking models, and preparing models for industry deployment using sparse matrices, customized transformers, and pipelines. By the end of the book, you'll be able to build high-performing machine learning models using XGBoost with minimal errors and maximum speed. What you will learn Build gradient boosting models from scratch Develop XGBoost regressors and classifiers with accuracy and speed Analyze variance and bias in terms of fine-tuning XGBoost hyperparameters Automatically correct missing values and scale imbalanced data Apply alternative base learners like dart, linear models, and XGBoost random forests Customize transformers and pipelines to deploy XGBoost models Build non-correlated ensembles and stack XGBoost models to increase accuracy Who this book is for This book is for data science professionals and enthusiasts, data analysts, and developers who want to build fast and accurate machine learning models that scale with big data. Proficiency in Python, along with a basic understanding of linear algebra, will help you to get the most out of this book.
Analytical Skills For Ai And Data Science
DOWNLOAD eBooks
Author : Daniel Vaughan
language : en
Publisher: O'Reilly Media
Release Date : 2020-05-21
Analytical Skills For Ai And Data Science written by Daniel Vaughan 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 2020-05-21 with Computers categories.
While several market-leading companies have successfully transformed their business models by following data- and AI-driven paths, the vast majority have yet to reap the benefits. How can your business and analytics units gain a competitive advantage by capturing the full potential of this predictive revolution? This practical guide presents a battle-tested end-to-end method to help you translate business decisions into tractable prescriptive solutions using data and AI as fundamental inputs. Author Daniel Vaughan shows data scientists, analytics practitioners, and others interested in using AI to transform their businesses not only how to ask the right questions but also how to generate value using modern AI technologies and decision-making principles. You’ll explore several use cases common to many enterprises, complete with examples you can apply when working to solve your own issues. Break business decisions into stages that can be tackled using different skills from the analytical toolbox Identify and embrace uncertainty in decision making and protect against common human biases Customize optimal decisions to different customers using predictive and prescriptive methods and technologies Ask business questions that create high value through AI- and data-driven technologies