Automated Machine Learning

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Mastering Automated Machine Learning Concepts Tools And Techniques

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Author : Peter Jones
language : en
Publisher: Walzone Press
Release Date : 2025-01-17

Mastering Automated Machine Learning Concepts Tools And Techniques written by Peter 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 2025-01-17 with Computers categories.

"Mastering Automated Machine Learning: Concepts, Tools, and Techniques" is an essential guide for anyone seeking to unlock the full potential of Automated Machine Learning (AutoML), a groundbreaking technology transforming the field of data science. By automating complex and time-consuming processes, AutoML is making machine learning more efficient and accessible to a broader range of professionals. This book offers an in-depth exploration of core principles, state-of-the-art methodologies, and the practical tools that define AutoML. From data preparation and feature engineering to model selection, tuning, and deployment, readers will acquire a thorough understanding of how AutoML streamlines the entire machine learning pipeline. Whether you're a data scientist, machine learning engineer, or software developer eager to harness the power of automation, "Mastering Automated Machine Learning" provides the insights you need to implement cutting-edge AutoML solutions. With practical examples and guidance on using Python-based frameworks, this book equips you to revolutionize your data science projects. Embrace the future of machine learning and optimize your workflows with "Mastering Automated Machine Learning: Concepts, Tools, and Techniques."

Automated Machine Learning

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Author : Frank Hutter
language : en
Publisher: Springer
Release Date : 2019-05-17

Automated Machine Learning written by Frank Hutter and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-17 with Computers categories.

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Automated Machine Learning

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Author : Joaquin Vanschoren
language : en
Publisher:
Release Date : 2020-10-08

Automated Machine Learning written by Joaquin Vanschoren and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-08 with Computers categories.

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work. This work was published by Saint Philip Street Press pursuant to a Creative Commons license permitting commercial use. All rights not granted by the work's license are retained by the author or authors.

Automated Machine Learning

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Author : Frank Hutter
language : en
Publisher:
Release Date : 2019

Automated Machine Learning written by Frank Hutter and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Machine learning categories.

This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.

Hands On Automated Machine Learning

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Author : Sibanjan Das
language : en
Publisher: Packt Publishing Ltd
Release Date : 2018-04-26

Hands On Automated Machine Learning written by Sibanjan Das 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 2018-04-26 with Computers categories.

Automate data and model pipelines for faster machine learning applications Key Features Build automated modules for different machine learning components Understand each component of a machine learning pipeline in depth Learn to use different open source AutoML and feature engineering platforms Book Description AutoML is designed to automate parts of Machine Learning. Readily available AutoML tools are making data science practitioners’ work easy and are received well in the advanced analytics community. Automated Machine Learning covers the necessary foundation needed to create automated machine learning modules and helps you get up to speed with them in the most practical way possible. In this book, you’ll learn how to automate different tasks in the machine learning pipeline such as data preprocessing, feature selection, model training, model optimization, and much more. In addition to this, it demonstrates how you can use the available automation libraries, such as auto-sklearn and MLBox, and create and extend your own custom AutoML components for Machine Learning. By the end of this book, you will have a clearer understanding of the different aspects of automated Machine Learning, and you’ll be able to incorporate automation tasks using practical datasets. You can leverage your learning from this book to implement Machine Learning in your projects and get a step closer to winning various machine learning competitions. What you will learn Understand the fundamentals of Automated Machine Learning systems Explore auto-sklearn and MLBox for AutoML tasks Automate your preprocessing methods along with feature transformation Enhance feature selection and generation using the Python stack Assemble individual components of ML into a complete AutoML framework Demystify hyperparameter tuning to optimize your ML models Dive into Machine Learning concepts such as neural networks and autoencoders Understand the information costs and trade-offs associated with AutoML Who this book is for If you’re a budding data scientist, data analyst, or Machine Learning enthusiast and are new to the concept of automated machine learning, this book is ideal for you. You’ll also find this book useful if you’re an ML engineer or data professional interested in developing quick machine learning pipelines for your projects. Prior exposure to Python programming will help you get the best out of this book.

Automated Machine Learning Automl

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Author : John Smith
language : en
Publisher: Independently Published
Release Date : 2024-04-28

Automated Machine Learning Automl written by John 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 2024-04-28 with Computers categories.

"Automated Machine Learning (AutoML): Concepts and Tools" is an indispensable resource for anyone looking to demystify the rapidly evolving technology of Automated Machine Learning. With the potential to revolutionize the field of data science by automating complex processes, AutoML is making machine learning more accessible and efficient than ever before. This book provides a comprehensive exploration of the foundational concepts, cutting-edge methodologies, and practical tools that make up AutoML. From data preparation and feature engineering to model selection and deployment, readers will gain in-depth knowledge of how AutoML simplifies the machine learning workflow. Whether you're a data scientist, a machine learning practitioner, or a software developer keen on leveraging the power of AutoML, this book is your guide to harnessing the full potential of automated solutions in Python and beyond. Embrace the future of machine learning and transform your data science projects with "Automated Machine Learning: Concepts and Tools."

Automated Machine Learning

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Author : Adnan Masood
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-02-18

Automated Machine Learning written by Adnan Masood 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 2021-02-18 with Computers categories.

Get to grips with automated machine learning and adopt a hands-on approach to AutoML implementation and associated methodologies Key FeaturesGet up to speed with AutoML using OSS, Azure, AWS, GCP, or any platform of your choiceEliminate mundane tasks in data engineering and reduce human errors in machine learning modelsFind out how you can make machine learning accessible for all users to promote decentralized processesBook Description Every machine learning engineer deals with systems that have hyperparameters, and the most basic task in automated machine learning (AutoML) is to automatically set these hyperparameters to optimize performance. The latest deep neural networks have a wide range of hyperparameters for their architecture, regularization, and optimization, which can be customized effectively to save time and effort. This book reviews the underlying techniques of automated feature engineering, model and hyperparameter tuning, gradient-based approaches, and much more. You'll discover different ways of implementing these techniques in open source tools and then learn to use enterprise tools for implementing AutoML in three major cloud service providers: Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform. As you progress, you’ll explore the features of cloud AutoML platforms by building machine learning models using AutoML. The book will also show you how to develop accurate models by automating time-consuming and repetitive tasks in the machine learning development lifecycle. By the end of this machine learning book, you’ll be able to build and deploy AutoML models that are not only accurate, but also increase productivity, allow interoperability, and minimize feature engineering tasks. What you will learnExplore AutoML fundamentals, underlying methods, and techniquesAssess AutoML aspects such as algorithm selection, auto featurization, and hyperparameter tuning in an applied scenarioFind out the difference between cloud and operations support systems (OSS)Implement AutoML in enterprise cloud to deploy ML models and pipelinesBuild explainable AutoML pipelines with transparencyUnderstand automated feature engineering and time series forecastingAutomate data science modeling tasks to implement ML solutions easily and focus on more complex problemsWho this book is for Citizen data scientists, machine learning developers, artificial intelligence enthusiasts, or anyone looking to automatically build machine learning models using the features offered by open source tools, Microsoft Azure Machine Learning, AWS, and Google Cloud Platform will find this book useful. Beginner-level knowledge of building ML models is required to get the best out of this book. Prior experience in using Enterprise cloud is beneficial.

Automated Machine Learning And Meta Learning For Multimedia

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Author : Wenwu Zhu
language : en
Publisher: Springer Nature
Release Date : 2022-01-01

Automated Machine Learning And Meta Learning For Multimedia written by Wenwu Zhu and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Computers categories.

This book disseminates and promotes the recent research progress and frontier development on AutoML and meta-learning as well as their applications on computer vision, natural language processing, multimedia and data mining related fields. These are exciting and fast-growing research directions in the general field of machine learning. The authors advocate novel, high-quality research findings, and innovative solutions to the challenging problems in AutoML and meta-learning. This topic is at the core of the scope of artificial intelligence, and is attractive to audience from both academia and industry. This book is highly accessible to the whole machine learning community, including: researchers, students and practitioners who are interested in AutoML, meta-learning, and their applications in multimedia, computer vision, natural language processing and data mining related tasks. The book is self-contained and designed for introductory and intermediate audiences. No special prerequisite knowledge is required to read this book.

Automated Machine Learning

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Author : Eric Scott
language : en
Publisher:
Release Date : 2025-08-25

Automated Machine Learning written by Eric Scott and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-25 with Computers categories.

Automated Machine Learning (AutoML) refers to the process of automating the end-to-end process of applying machine learning to real-world problems. It involves developing algorithms and systems that automatically handle tasks such as data preprocessing, feature engineering, model selection, hyperparameter tuning, and model evaluation. AutoML aims to simplify and accelerate the machine learning workflow, making it accessible to users without extensive expertise in data science or machine learning. Techniques used in AutoML include meta-learning, Bayesian optimization, and evolutionary algorithms to efficiently search and optimise models and their parameters. AutoML reduces the manual effort required to build and deploy machine learning models, thereby democratising access to powerful predictive tools across various industries. AutoML continues to evolve with advancements in algorithm design and computational efficiency, driving innovation in machine learning applications. This book provides comprehensive insights into the field of automated machine learning. The topics included in this book on artificial intelligence are of utmost significance and bound to provide incredible insights to readers. It is an essential guide for both academicians and those who wish to pursue this discipline further.

Automated Machine Learning With Microsoft Azure

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Author : Dennis Michael Sawyers
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-04-23

Automated Machine Learning With Microsoft Azure written by Dennis Michael Sawyers 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 2021-04-23 with Computers categories.

A practical, step-by-step guide to using Microsoft's AutoML technology on the Azure Machine Learning service for developers and data scientists working with the Python programming language Key FeaturesCreate, deploy, productionalize, and scale automated machine learning solutions on Microsoft AzureImprove the accuracy of your ML models through automatic data featurization and model trainingIncrease productivity in your organization by using artificial intelligence to solve common problemsBook Description Automated Machine Learning with Microsoft Azure will teach you how to build high-performing, accurate machine learning models in record time. It will equip you with the knowledge and skills to easily harness the power of artificial intelligence and increase the productivity and profitability of your business. Guided user interfaces (GUIs) enable both novices and seasoned data scientists to easily train and deploy machine learning solutions to production. Using a careful, step-by-step approach, this book will teach you how to use Azure AutoML with a GUI as well as the AzureML Python software development kit (SDK). First, you'll learn how to prepare data, train models, and register them to your Azure Machine Learning workspace. You'll then discover how to take those models and use them to create both automated batch solutions using machine learning pipelines and real-time scoring solutions using Azure Kubernetes Service (AKS). Finally, you will be able to use AutoML on your own data to not only train regression, classification, and forecasting models but also use them to solve a wide variety of business problems. By the end of this Azure book, you'll be able to show your business partners exactly how your ML models are making predictions through automatically generated charts and graphs, earning their trust and respect. What you will learnUnderstand how to train classification, regression, and forecasting ML algorithms with Azure AutoMLPrepare data for Azure AutoML to ensure smooth model training and deploymentAdjust AutoML configuration settings to make your models as accurate as possibleDetermine when to use a batch-scoring solution versus a real-time scoring solutionProductionalize your AutoML and discover how to quickly deliver valueCreate real-time scoring solutions with AutoML and Azure Kubernetes ServiceTrain a large number of AutoML models at once using the AzureML Python SDKWho this book is for Data scientists, aspiring data scientists, machine learning engineers, or anyone interested in applying artificial intelligence or machine learning in their business will find this machine learning book useful. You need to have beginner-level knowledge of artificial intelligence and a technical background in computer science, statistics, or information technology before getting started. Familiarity with Python will help you implement the more advanced features found in the chapters, but even data analysts and SQL experts will be able to train ML models after finishing this book.