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Hands On Machine Learning With Scikit Learn Keras And Tensorflow 2nd Edition


Hands On Machine Learning With Scikit Learn Keras And Tensorflow 2nd Edition
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Download Hands On Machine Learning With Scikit Learn Keras And Tensorflow 2nd Edition 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 And Tensorflow 2nd Edition 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


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 2nd Edition


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.



Kubeflow For Machine Learning


Kubeflow For Machine Learning
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Author : Trevor Grant
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2020-10-13

Kubeflow For Machine Learning written by Trevor Grant 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 2020-10-13 with Computers categories.


If you're training a machine learning model but aren't sure how to put it into production, this book will get you there. Kubeflow provides a collection of cloud native tools for different stages of a model's lifecycle, from data exploration, feature preparation, and model training to model serving. This guide helps data scientists build production-grade machine learning implementations with Kubeflow and shows data engineers how to make models scalable and reliable. Using examples throughout the book, authors Holden Karau, Trevor Grant, Ilan Filonenko, Richard Liu, and Boris Lublinsky explain how to use Kubeflow to train and serve your machine learning models on top of Kubernetes in the cloud or in a development environment on-premises. Understand Kubeflow's design, core components, and the problems it solves Understand the differences between Kubeflow on different cluster types Train models using Kubeflow with popular tools including Scikit-learn, TensorFlow, and Apache Spark Keep your model up to date with Kubeflow Pipelines Understand how to capture model training metadata Explore how to extend Kubeflow with additional open source tools Use hyperparameter tuning for training Learn how to serve your model in production



Hands On Machine Learning With Scikit Learn Keras And Tensorflow


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



Machine Learning With Python


Machine Learning With Python
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Author : Tarkeshwar Barua
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2024-09-03

Machine Learning With Python written by Tarkeshwar Barua and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-03 with Computers categories.


This book explains how to use the programming language Python to develop machine learning and deep learning tasks. It provides readers with a solid foundation in the fundamentals of machine learning algorithms and techniques. The book covers a wide range of topics, including data preprocessing, supervised and unsupervised learning, model evaluation, and deployment. By leveraging the power of Python, readers will gain the practical skills necessary to build and deploy effective machine learning models, making this book an invaluable resource for anyone interested in exploring the exciting world of artificial intelligence.



Exploration Of Transformative Technologies In Healthcare 6 0


Exploration Of Transformative Technologies In Healthcare 6 0
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Author : Kumar, Piyush
language : en
Publisher: IGI Global
Release Date : 2025-03-14

Exploration Of Transformative Technologies In Healthcare 6 0 written by Kumar, Piyush and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-14 with Medical categories.


In recent years, the rapid advancement of technology has revolutionized industries worldwide. Innovations such as artificial intelligence (AI), machine learning, telemedicine, blockchain, and advanced robotics enhance the precision and efficiency of medical practices while democratizing access to care, improving patient outcomes, and reducing costs. Healthcare 6.0 is marked by a shift towards more personalized, data-driven, and patient-centered approaches, challenging traditional models and paving the way for a more inclusive and sustainable healthcare system. Further exploration of the current state of these technologies may reveal their future potential and the ethical and regulatory considerations they bring. Exploration of Transformative Technologies in Healthcare 6.0 explores medical technologies and their integration and effective use in healthcare. It examines how healthcare managers can effectively lead their organizations by embracing technology, focusing on patient-centered care, leveraging data, promoting preventive care, fostering collaboration, and staying abreast of regulatory changes. This book covers topics such as medical devices, blockchain, and smart hospitals, and is a useful resource for medical and healthcare professionals, data scientists, computer engineers, academicians, and researchers.



The Art Of Ai Product Development


The Art Of Ai Product Development
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Author : Janna Lipenkova
language : en
Publisher: Simon and Schuster
Release Date : 2025-06-24

The Art Of Ai Product Development written by Janna Lipenkova 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 2025-06-24 with Computers categories.


A hands-on guide for delivering value with AI-driven products! Learn how AI can improve content creation, accelerate data analysis, and upgrade process automation. The Art of AI Product Development offers a clear, practical approach to creating products that use AI. It provides real-world guidance on defining your AI strategy, developing useful AI features, and supporting user trust and adoption. Rather than chasing trends, the book focuses on core principles and long-term thinking—foundations that remain relevant as the field evolves. Inside The Art of AI Product Development, you will learn vital skills for the effective use of AI, including: • Identifying market and business opportunities for AI • Gaining an in-depth understanding of modern AI approaches, incl. predictive AI, LLMs, Retrieval-Augmented Generation, and agent systems • Assembling AI solutions that work, without the hype • Efficiently communicating with data scientists and ML engineers • Designing user-friendly AI interfaces that emphasize trust and transparency • Implementing safe, ethical AI with proper governance processes The Art of AI Product Development is written for product managers, tech executives, UX designers, and anyone responsible for the success of an AI-driven product. It introduces a broad spectrum of AI opportunities and case studies from different domains such as marketing, supply chain, and logistics. You’ll carefully progress from initial design conversations, through to efficient and secure development, and on to deployment and day-to-day management of AI-driven applications. About the technology Integrating AI into your software and processes can create real value for your business and its customers—if you do it right. When you’re on the hook for delivering AI-enabled products, you’ll need to spot high-impact opportunities, work effectively with engineers, design user-centric features, avoid common project failures, and manage real-world launches. This book shows you how. About the book The Art of AI Product Development gives you a clear framework, practical tools, and real-world examples to build confidence and succeed with new AI projects—even if you’re tackling AI for the first time. You’ll love the practical use cases and end-to-end scenarios from domains such as marketing, supply chain management, and sustainability. What's inside • Ideate, shape, and prioritize AI opportunities • Develop AI systems with techniques such as prompt engineering, RAG, and predictive AI • Communicate with different AI stakeholders and promote AI adoption About the reader Written for software product managers, business-oriented engineers, UX designers, startup founders, and anyone responsible for developing, designing, or marketing AI products. No experience with AI required. About the author Dr. Janna Lipenkova is the founder of an AI and analytics business where she has successfully managed AI projects for world-class companies like BMW, Lufthansa, and Volkswagen. Table of Contents Part 1 1 Creating value with AI-driven products 2 Discovering and prioritizing AI opportunities 3 Mapping the AI solution space Part 2 4 Predictive AI 5 Exploring and evaluating language models 6 Prompt engineering 7 Search and retrieval-augmented generation 8 Fine-tuning language models 9 Automating workflows with agentic AI Part 3 10 AI user experience: Designing for uncertainty 11 AI governance 12 Working with your stakeholders Appendix A AI development toolbox



Industry 4 0 Technologies For Business Excellence


Industry 4 0 Technologies For Business Excellence
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Author : Shivani Bali
language : en
Publisher: CRC Press
Release Date : 2021-12-31

Industry 4 0 Technologies For Business Excellence written by Shivani Bali and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-12-31 with Business & Economics categories.


This book captures deploying Industry 4.0 technologies for business excellence and moving towards Society 5.0. It addresses applications of Industry 4.0 in the areas of marketing, operations, supply chain, finance, and HR to achieve business excellence. Industry 4.0 Technologies for Business Excellence: Frameworks, Practices, and Applications focuses on the use of AI in management across different sectors. It explores the benefits through a human-centered approach to resolving social problems by integrating cyberspace and physical space. It discusses the framework for moving towards Society 5.0 and keeping a balance between economic and social gains. This book brings together researchers, developers, practitioners, and users interested in exploring new ideas, techniques, and tools and exchanging their experiences to provide the most recent information on Industry 4.0 applications in the field of business excellence. Graduate or postgraduate students, professionals, and researchers in the fields of operations management, manufacturing, healthcare, supply chain, marketing, finance, and HR will find this book full of new ideas, techniques, and tools related to Industry 4.0.



Tinyml


Tinyml
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Author : Pete Warden
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2019-12-16

Tinyml written by Pete Warden 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 2019-12-16 with Computers categories.


Deep learning networks are getting smaller. Much smaller. The Google Assistant team can detect words with a model just 14 kilobytes in size—small enough to run on a microcontroller. With this practical book you’ll enter the field of TinyML, where deep learning and embedded systems combine to make astounding things possible with tiny devices. Pete Warden and Daniel Situnayake explain how you can train models small enough to fit into any environment. Ideal for software and hardware developers who want to build embedded systems using machine learning, this guide walks you through creating a series of TinyML projects, step-by-step. No machine learning or microcontroller experience is necessary. Build a speech recognizer, a camera that detects people, and a magic wand that responds to gestures Work with Arduino and ultra-low-power microcontrollers Learn the essentials of ML and how to train your own models Train models to understand audio, image, and accelerometer data Explore TensorFlow Lite for Microcontrollers, Google’s toolkit for TinyML Debug applications and provide safeguards for privacy and security Optimize latency, energy usage, and model and binary size



Core Concepts In Statistical Learning


Core Concepts In Statistical Learning
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Author : Tushar Gulati
language : en
Publisher: Educohack Press
Release Date : 2025-02-20

Core Concepts In Statistical Learning written by Tushar Gulati and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.


"Core Concepts in Statistical Learning" serves as a comprehensive introduction to fundamental techniques and concepts in statistical learning, tailored specifically for undergraduates in the United States. This book covers a broad range of topics essential for students looking to understand the intersection of statistics, data science, and machine learning. The book explores major topics, including supervised and unsupervised learning, model selection, and the latest algorithms in predictive analytics. Each chapter delves into methods like decision trees, neural networks, and support vector machines, ensuring readers grasp theoretical concepts and apply them to practical data analysis problems. Designed to be student-friendly, the text incorporates numerous examples, graphical illustrations, and real-world data sets to facilitate a deeper understanding of the material. Structured to support both classroom learning and self-study, it is a versatile resource for students across disciplines such as economics, biology, engineering, and more. Whether you're an aspiring data scientist or looking to enhance your analytical skills, "Core Concepts in Statistical Learning" provides the tools needed to navigate the complex landscape of modern data analysis and predictive modeling.