Machine Learning Production Systems
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Machine Learning Production Systems
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Author : Robert Crowe
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-02
Machine Learning Production Systems written by Robert Crowe 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 2024-10-02 with Computers categories.
Using machine learning for products, services, and critical business processes is quite different from using ML in an academic or research setting—especially for recent ML graduates and those moving from research to a commercial environment. Whether you currently work to create products and services that use ML, or would like to in the future, this practical book gives you a broad view of the entire field. Authors Robert Crowe, Hannes Hapke, Emily Caveness, and Di Zhu help you identify topics that you can dive into deeper, along with reference materials and tutorials that teach you the details. You'll learn the state of the art of machine learning engineering, including a wide range of topics such as modeling, deployment, and MLOps. You'll learn the basics and advanced aspects to understand the production ML lifecycle. This book provides four in-depth sections that cover all aspects of machine learning engineering: Data: collecting, labeling, validating, automation, and data preprocessing; data feature engineering and selection; data journey and storage Modeling: high performance modeling; model resource management techniques; model analysis and interoperability; neural architecture search Deployment: model serving patterns and infrastructure for ML models and LLMs; management and delivery; monitoring and logging Productionalizing: ML pipelines; classifying unstructured texts and images; genAI model pipelines
Machine Learning Production Systems
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Author : Robert Crowe (Data scientist)
language : en
Publisher:
Release Date : 2025
Machine Learning Production Systems written by Robert Crowe (Data scientist) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025 with Artificial intelligence categories.
Machine Learning Production Systems
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Author : Robert Crowe
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-10-02
Machine Learning Production Systems written by Robert Crowe 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 2024-10-02 with Computers categories.
Using machine learning for products, services, and critical business processes is quite different from using ML in an academic or research setting—especially for recent ML graduates and those moving from research to a commercial environment. Whether you currently work to create products and services that use ML, or would like to in the future, this practical book gives you a broad view of the entire field. Authors Robert Crowe, Hannes Hapke, Emily Caveness, and Di Zhu help you identify topics that you can dive into deeper, along with reference materials and tutorials that teach you the details. You'll learn the state of the art of machine learning engineering, including a wide range of topics such as modeling, deployment, and MLOps. You'll learn the basics and advanced aspects to understand the production ML lifecycle. This book provides four in-depth sections that cover all aspects of machine learning engineering: Data: collecting, labeling, validating, automation, and data preprocessing; data feature engineering and selection; data journey and storage Modeling: high performance modeling; model resource management techniques; model analysis and interoperability; neural architecture search Deployment: model serving patterns and infrastructure for ML models and LLMs; management and delivery; monitoring and logging Productionalizing: ML pipelines; classifying unstructured texts and images; genAI model pipelines
Machine Learning Engineering With Python
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Author : Andrew P. McMahon
language : en
Publisher: Packt Publishing Ltd
Release Date : 2021-11-05
Machine Learning Engineering With Python written by Andrew P. McMahon 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 2021-11-05 with Computers categories.
Supercharge the value of your machine learning models by building scalable and robust solutions that can serve them in production environments Key Features Explore hyperparameter optimization and model management tools Learn object-oriented programming and functional programming in Python to build your own ML libraries and packages Explore key ML engineering patterns like microservices and the Extract Transform Machine Learn (ETML) pattern with use cases Book DescriptionMachine learning engineering is a thriving discipline at the interface of software development and machine learning. This book will help developers working with machine learning and Python to put their knowledge to work and create high-quality machine learning products and services. Machine Learning Engineering with Python takes a hands-on approach to help you get to grips with essential technical concepts, implementation patterns, and development methodologies to have you up and running in no time. You'll begin by understanding key steps of the machine learning development life cycle before moving on to practical illustrations and getting to grips with building and deploying robust machine learning solutions. As you advance, you'll explore how to create your own toolsets for training and deployment across all your projects in a consistent way. The book will also help you get hands-on with deployment architectures and discover methods for scaling up your solutions while building a solid understanding of how to use cloud-based tools effectively. Finally, you'll work through examples to help you solve typical business problems. By the end of this book, you'll be able to build end-to-end machine learning services using a variety of techniques and design your own processes for consistently performant machine learning engineering.What you will learn Find out what an effective ML engineering process looks like Uncover options for automating training and deployment and learn how to use them Discover how to build your own wrapper libraries for encapsulating your data science and machine learning logic and solutions Understand what aspects of software engineering you can bring to machine learning Gain insights into adapting software engineering for machine learning using appropriate cloud technologies Perform hyperparameter tuning in a relatively automated way Who this book is for This book is for machine learning engineers, data scientists, and software developers who want to build robust software solutions with machine learning components. If you're someone who manages or wants to understand the production life cycle of these systems, you'll find this book useful. Intermediate-level knowledge of Python is necessary.
Machine Learning For Networking
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Author : Éric Renault
language : en
Publisher: Springer
Release Date : 2019-05-10
Machine Learning For Networking written by Éric Renault and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-05-10 with Computers categories.
This book constitutes the thoroughly refereed proceedings of the First International Conference on Machine Learning for Networking, MLN 2018, held in Paris, France, in November 2018. The 22 revised full papers included in the volume were carefully reviewed and selected from 48 submissions. They present new trends in the following topics: Deep and reinforcement learning; Pattern recognition and classification for networks; Machine learning for network slicing optimization, 5G system, user behavior prediction, multimedia, IoT, security and protection; Optimization and new innovative machine learning methods; Performance analysis of machine learning algorithms; Experimental evaluations of machine learning; Data mining in heterogeneous networks; Distributed and decentralized machine learning algorithms; Intelligent cloud-support communications, resource allocation, energy-aware/green communications, software defined networks, cooperative networks, positioning and navigation systems, wireless communications, wireless sensor networks, underwater sensor networks.
Designing Machine Learning Systems
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Author : Chip Huyen
language : en
Publisher: O'Reilly Media
Release Date : 2022-06-30
Designing Machine Learning Systems written by Chip Huyen 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 2022-06-30 with Computers categories.
Many tutorials show you how to develop ML systems from ideation to deployed models. But with constant changes in tooling, those systems can quickly become outdated. Without an intentional design to hold the components together, these systems will become a technical liability, prone to errors and be quick to fall apart. In this book, Chip Huyen provides a framework for designing real-world ML systems that are quick to deploy, reliable, scalable, and iterative. These systems have the capacity to learn from new data, improve on past mistakes, and adapt to changing requirements and environments. You�?�¢??ll learn everything from project scoping, data management, model development, deployment, and infrastructure to team structure and business analysis. Learn the challenges and requirements of an ML system in production Build training data with different sampling and labeling methods Leverage best techniques to engineer features for your ML models to avoid data leakage Select, develop, debug, and evaluate ML models that are best suit for your tasks Deploy different types of ML systems for different hardware Explore major infrastructural choices and hardware designs Understand the human side of ML, including integrating ML into business, user experience, and team structure
Technological Innovation For Value Creation
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Author : Luis M. Camarinha-Matos
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-02-03
Technological Innovation For Value Creation written by Luis M. Camarinha-Matos and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-03 with Business & Economics categories.
This book constitutes the refereed proceedings of the Third IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2012, held in Costa de Caparica, Portugal, in February 2012. The 65 revised full papers were carefully reviewed and selected from numerous submissions. They cover a wide spectrum of topics ranging from collaborative enterprise networks to microelectronics. The papers are organized in topical sections on collaborative systems, service orientation, knowledge and content management, human interaction, Petri nets, smart systems, robotic systems, perceptional systems, signal processing, energy, renewable energy, energy smart grid, power electronics, electronics, optimization in electronics, telecommunications and electronics, and electronic materials. The book also includes papers from the Workshop on Data Anaylsis and Modeling Retina in Health and Disease.
Artificial Intelligence And Machine Learning For Real World Applications
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Author : Latesh Malik
language : en
Publisher: CRC Press
Release Date : 2025-10-16
Artificial Intelligence And Machine Learning For Real World Applications written by Latesh Malik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-16 with Computers categories.
This book introduces foundational and advanced concepts in artificial intelligence (AI) and machine learning (ML), focusing on their real-world applications and societal implications. Covering topics from knowledge representation and model interpretability to deep learning and generative AI, Artificial Intelligence and Machine Learning for Real-World Applications: A Beginner's Guide with Case Studies includes practical Python implementations and case studies from healthcare, agriculture, and education. Beginning with core concepts such as AI fundamentals, knowledge representation, and statistical techniques, the text gradually advances to cover ML algorithms, deep learning architectures, and the basics of generative AI. Detailed discussions of data preprocessing, model training, evaluation metrics, and Python-based implementation make this book both practical and accessible. Offers real-world examples and case studies illustrating the societal impact and practical applications of AI and ML technologies Discusses data preprocessing techniques, model selection, and evaluation metrics with practical implementation in Python and in detail Explores AI problem-solving processes, knowledge representation, and model training strategies, catering to readers with varying levels of technical expertise Covers AI and ML principles spanning statistical techniques, ML algorithms, deep learning structures, and generative AI basics Focuses on societal applications in healthcare, agriculture, and education, addressing challenges faced by the elderly and special needs individuals This book is for professionals, researchers, and scholars interested in the application of AI and ML.
Advances In Sustainable And Competitive Manufacturing Systems
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Author : Américo Azevedo
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-06-25
Advances In Sustainable And Competitive Manufacturing Systems written by Américo Azevedo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-25 with Technology & Engineering categories.
The proceedings includes the set of revised papers from the 23rd International Conference on Flexible Automation and Intelligent Manufacturing (FAIM 2013). This conference aims to provide an international forum for the exchange of leading edge scientific knowledge and industrial experience regarding the development and integration of the various aspects of Flexible Automation and Intelligent Manufacturing Systems covering the complete life-cycle of a company’s Products and Processes. Contents will include topics such as: Product, Process and Factory Integrated Design, Manufacturing Technology and Intelligent Systems, Manufacturing Operations Management and Optimization and Manufacturing Networks and MicroFactories.
Technological Innovation For The Internet Of Things
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Author : Luis M. Camarinha-Matos
language : en
Publisher: Springer
Release Date : 2013-04-15
Technological Innovation For The Internet Of Things written by Luis M. Camarinha-Matos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-15 with Computers categories.
This book constitutes the refereed proceedings of the 4th IFIP WG 5.5/SOCOLNET Doctoral Conference on Computing, Electrical and Industrial Systems, DoCEIS 2013, held in Costa de Caparica, Portugal, in April 2013. The 69 revised full papers were carefully reviewed and selected from numerous submissions. They cover a wide spectrum of topics ranging from collaborative enterprise networks to microelectronics. The papers are organized in the following topical sections: collaborative enterprise networks; service orientation; intelligent computational systems; computational systems; computational systems applications; perceptional systems; robotics and manufacturing; embedded systems and Petri nets; control and decision; integration of power electronics systems with ICT; energy generation; energy distribution; energy transformation; optimization techniques in energy; telecommunications; electronics: devices design; electronics: amplifiers; electronics: RF applications; and electronics: applications.