Feature Engineering Design Patterns For Machine Learning
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Feature Engineering Design Patterns For Machine Learning
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Author : Todd Chandler
language : en
Publisher: Independently Published
Release Date : 2025-09
Feature Engineering Design Patterns For Machine Learning written by Todd Chandler and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09 with Computers categories.
Feature Engineering Design Patterns for Machine Learning: Unlock Proven Pipelines and Scalable Solutions to Transform Raw Data into Predictive Power Struggling to turn messy data into reliable predictive features that survive production realities? Feature Engineering Design Patterns for Machine Learning offers a practical, pattern-first playbook for building feature pipelines that scale, are auditable, and actually improve model performance. This book presents proven, production-ready design patterns for feature engineering: how to construct point-in-time correct temporal features, encode high-cardinality categories safely, build robust text and embedding features, automate feature factories, and integrate features into MLOps workflows. It focuses on concrete, repeatable engineering practices, templates, tests, and deployment strategies, that make feature work reproducible and low-risk. What you'll get from this book You will learn how to build feature engineering systems that are maintainable, explainable, and production-ready. Specifically, you will gain the skills to: Create point-in-time, leakage-free feature materializations and backtests for realistic evaluation. Encode categorical, temporal, and text signals at scale using target smoothing, hashing, EWMA, and embedding patterns. Compose modular feature pipelines (pandas, scikit-learn, PySpark) and parameterize templates for rapid, safe feature generation. Integrate features with feature stores, online serving, and CI/CD while versioning code, schemas, and artifacts. Detect and respond to feature drift, establish monitoring and audit trails, and retire features with confidence. Apply interpretability tools (SHAP, permutation importance) and selection strategies that balance performance, stability, and cost. Packed with checklists, template code, and real-world blueprints from finance, retail, and customer support, this is a hands-on manual for ML engineers, data scientists, and software teams who need reliable feature pipelines, not theoretical fluff. Ready to replace fragile experiments with repeatable engineering? Get your copy of Feature Engineering Design Patterns for Machine Learning and start turning raw data into durable predictive power today.
Machine Learning Design Patterns
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Author : Valliappa Lakshmanan
language : en
Publisher: O'Reilly Media
Release Date : 2020-10-15
Machine Learning Design Patterns written by Valliappa Lakshmanan 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 2020-10-15 with Computers categories.
The design patterns in this book capture best practices and solutions to recurring problems in machine learning. The authors, three Google engineers, catalog proven methods to help data scientists tackle common problems throughout the ML process. These design patterns codify the experience of hundreds of experts into straightforward, approachable advice. In this book, you will find detailed explanations of 30 patterns for data and problem representation, operationalization, repeatability, reproducibility, flexibility, explainability, and fairness. Each pattern includes a description of the problem, a variety of potential solutions, and recommendations for choosing the best technique for your situation. You'll learn how to: Identify and mitigate common challenges when training, evaluating, and deploying ML models Represent data for different ML model types, including embeddings, feature crosses, and more Choose the right model type for specific problems Build a robust training loop that uses checkpoints, distribution strategy, and hyperparameter tuning Deploy scalable ML systems that you can retrain and update to reflect new data Interpret model predictions for stakeholders and ensure models are treating users fairly
Machine Learning By Design
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Author : Peng Shao (Computer scientist)
language : en
Publisher:
Release Date : 2024
Machine Learning By Design written by Peng Shao (Computer scientist) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024 with Machine learning categories.
Software Architecture
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Author : Matthias Galster
language : en
Publisher: Springer Nature
Release Date : 2024-08-31
Software Architecture written by Matthias Galster and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-31 with Computers categories.
This book constitutes the refereed proceedings of the 18th European Conference on Software Architecture, ECSA 2024, held in Luxembourg City, Luxembourg, during September 2–6, 2024. The 14 full research papers, 3 experience report papers, 7 short papers and 3 industry papers included in this book were carefully reviewed and selected from 89 submissions They were organized in topical sections as follows: Architecture modeling and design; Architecture evaluation; Microservices architecture; Sustainability; Trustworthiness; Architecture decision making; and Architecture documentation.
Data Algorithms With Spark
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Author : Mahmoud Parsian
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2022-04-08
Data Algorithms With Spark written by Mahmoud Parsian 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 2022-04-08 with Computers categories.
Apache Spark's speed, ease of use, sophisticated analytics, and multilanguage support makes practical knowledge of this cluster-computing framework a required skill for data engineers and data scientists. With this hands-on guide, anyone looking for an introduction to Spark will learn practical algorithms and examples using PySpark. In each chapter, author Mahmoud Parsian shows you how to solve a data problem with a set of Spark transformations and algorithms. You'll learn how to tackle problems involving ETL, design patterns, machine learning algorithms, data partitioning, and genomics analysis. Each detailed recipe includes PySpark algorithms using the PySpark driver and shell script. With this book, you will: Learn how to select Spark transformations for optimized solutions Explore powerful transformations and reductions including reduceByKey(), combineByKey(), and mapPartitions() Understand data partitioning for optimized queries Build and apply a model using PySpark design patterns Apply motif-finding algorithms to graph data Analyze graph data by using the GraphFrames API Apply PySpark algorithms to clinical and genomics data Learn how to use and apply feature engineering in ML algorithms Understand and use practical and pragmatic data design patterns
Objects Data Ai
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Author : Reeshabh Choudhary
language : en
Publisher: Reeshabh Choudhary
Release Date : 2023-11-10
Objects Data Ai written by Reeshabh Choudhary and has been published by Reeshabh Choudhary this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Computers categories.
This book is about uncovering a journey of how Software programming evolved and AI based technologies came into foray. This book tries to connect the dots for a new programmer, starting on his/her journey into the software development world. With so many technologies evolving around every single day, with new breaches in innovation in the field of AI/ML or Data Science, which gets the job done in a whisker, as programmers we tend to think, where do we stand? The journey or even the thought of making sense of everything around us can be quite overwhelming. From the days of C/C++ programming to Java/C#/JavaScript and Python/MATLAB/R, programming has exponentially evolved. And so, does the computational ability of computers, which also helped in faster execution of these programs, but also to extraction of Information from the data generated via the applications developed by these programs. In this digital age, everything seems to be connected and yet we sweat making sense of all these connections. In the interconnected digital age, understanding the connections between various technologies can be challenging. The book aims to bridge some of these gaps by providing readers with a foundational understanding of how programming, data, and machine learning are interconnected. By grasping these fundamentals, software developers can connect the dots according to their specific requirements.
Software Engineering And Advanced Applications
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Author : Davide Taibi
language : en
Publisher: Springer Nature
Release Date : 2025-10-09
Software Engineering And Advanced Applications written by Davide Taibi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-10-09 with Computers categories.
This three-volume set constitutes the refereed proceedings of the 51st Euromicro Conference on Software Engineering and Advanced Applications, SEAA 2025, held in Salerno, Italy, during September 10-12, 2025. The 62 full papers were carefully reviewed and selected from 177 submissions.These papers were organized in the following topical sections: Part I: Data and AI Driven Engineering; Cyber-Physical Systems; Model-Driven Engineering and Modeling Languages. Part II: Practical Aspects of Software Engineering; Systematic Literature Reviews and Mapping Studies in Software Engineering. Part III: Software Management: Measurement, Peopleware, and Innovation; Software Process and Product Improvement; Software Analytics: Mining Software Open Datasets and Repositories; Emerging Computing Technologies.
Feast Spark Engineering Essentials
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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-24
Feast Spark Engineering Essentials written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-24 with Computers categories.
"Feast-Spark Engineering Essentials" Feast-Spark Engineering Essentials is a comprehensive guide that bridges the latest advances in feature engineering with production-grade machine learning operations. The book delves deep into the architectural foundations of Feast as a feature store and Apache Spark as a distributed data processing engine, offering a detailed understanding of how their integration empowers scalable, reliable ML pipelines. Readers are introduced to the critical motivations driving Feast-Spark synergy, with clear explanations of data modeling, entity design, and the practicalities of end-to-end pipeline orchestration that meet the demands of modern MLOps. Through meticulously structured chapters, the book covers the entire feature engineering lifecycle, from creation, extraction, and transformation to advanced topics like automated validation, versioning, and drift detection. It discusses robust engineering practices for both batch and real-time ingestion, optimized transformations, and operational best practices required to build and maintain large-scale feature pipelines. Special attention is given to storage backends, high availability, resource scaling, and multi-region deployments, ensuring that enterprises can confidently implement reliable and cost-effective solutions. Feast-Spark Engineering Essentials stands out by addressing not only technical integration but also the operational realities of security, privacy, and compliance in regulated industries. Real-world case studies and emerging patterns provide actionable insight for both engineers and architects, encompassing governance, observability, cross-team collaboration, and the future evolution of feature store technology. The book is an indispensable resource for anyone building, operating, or scaling feature engineering infrastructure at the intersection of data and machine learning.
Web Engineering
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Author : Jordi Cabot
language : en
Publisher: Springer
Release Date : 2017-05-30
Web Engineering written by Jordi Cabot and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-30 with Computers categories.
This book constitutes the refereed proceedings of the 17th International Conference on Web Engineering, ICWE 2017, held in Rome, Italy, in June 2017. The 20 full research papers and 12 short papers presented together with 6 application papers, 6 demonstration papers, and 6 contributions to the PhD Symposium, were carefully reviewed and selected from 139 submissions. The papers cover research areas such as Web application modeling and engineering, human computation and crowdsourcing applications, Web applications composition and mashup, Social Web applications, Semantic Web applications, Web of Things applications, and big data.
Handbook Of Research On Engineering Innovations And Technology Management In Organizations
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Author : Gaur, Loveleen
language : en
Publisher: IGI Global
Release Date : 2020-04-17
Handbook Of Research On Engineering Innovations And Technology Management In Organizations written by Gaur, Loveleen and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-17 with Technology & Engineering categories.
As technology weaves itself more tightly into everyday life, socio-economic development has become intricately tied to these ever-evolving innovations. Technology management is now an integral element of sound business practices, and this revolution has opened up many opportunities for global communication. However, such swift change warrants greater research that can foresee and possibly prevent future complications within and between organizations. The Handbook of Research on Engineering Innovations and Technology Management in Organizations is a collection of innovative research that explores global concerns in the applications of technology to business and the explosive growth that resulted. Highlighting a wide range of topics such as cyber security, legal practice, and artificial intelligence, this book is ideally designed for engineers, manufacturers, technology managers, technology developers, IT specialists, productivity consultants, executives, lawyers, programmers, managers, policymakers, academicians, researchers, and students.