Implementing Mlops In The Enterprise

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Implementing Mlops In The Enterprise

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Author : Yaron Haviv
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-11-30

Implementing Mlops In The Enterprise written by Yaron Haviv 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 2023-11-30 with Computers categories.

With demand for scaling, real-time access, and other capabilities, businesses need to consider building operational machine learning pipelines. This practical guide helps your company bring data science to life for different real-world MLOps scenarios. Senior data scientists, MLOps engineers, and machine learning engineers will learn how to tackle challenges that prevent many businesses from moving ML models to production. Authors Yaron Haviv and Noah Gift take a production-first approach. Rather than beginning with the ML model, you'll learn how to design a continuous operational pipeline, while making sure that various components and practices can map into it. By automating as many components as possible, and making the process fast and repeatable, your pipeline can scale to match your organization's needs. You'll learn how to provide rapid business value while answering dynamic MLOps requirements. This book will help you: Learn the MLOps process, including its technological and business value Build and structure effective MLOps pipelines Efficiently scale MLOps across your organization Explore common MLOps use cases Build MLOps pipelines for hybrid deployments, real-time predictions, and composite AI Learn how to prepare for and adapt to the future of MLOps Effectively use pre-trained models like HuggingFace and OpenAI to complement your MLOps strategy

Responsible Ai In The Enterprise

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Author : Adnan Masood
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-07-31

Responsible Ai In The Enterprise 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 2023-07-31 with Computers categories.

Build and deploy your AI models successfully by exploring model governance, fairness, bias, and potential pitfalls Purchase of the print or Kindle book includes a free PDF eBook Key Features Learn ethical AI principles, frameworks, and governance Understand the concepts of fairness assessment and bias mitigation Introduce explainable AI and transparency in your machine learning models Book DescriptionResponsible AI in the Enterprise is a comprehensive guide to implementing ethical, transparent, and compliant AI systems in an organization. With a focus on understanding key concepts of machine learning models, this book equips you with techniques and algorithms to tackle complex issues such as bias, fairness, and model governance. Throughout the book, you’ll gain an understanding of FairLearn and InterpretML, along with Google What-If Tool, ML Fairness Gym, IBM AI 360 Fairness tool, and Aequitas. You’ll uncover various aspects of responsible AI, including model interpretability, monitoring and management of model drift, and compliance recommendations. You’ll gain practical insights into using AI governance tools to ensure fairness, bias mitigation, explainability, privacy compliance, and privacy in an enterprise setting. Additionally, you’ll explore interpretability toolkits and fairness measures offered by major cloud AI providers like IBM, Amazon, Google, and Microsoft, while discovering how to use FairLearn for fairness assessment and bias mitigation. You’ll also learn to build explainable models using global and local feature summary, local surrogate model, Shapley values, anchors, and counterfactual explanations. By the end of this book, you’ll be well-equipped with tools and techniques to create transparent and accountable machine learning models.What you will learn Understand explainable AI fundamentals, underlying methods, and techniques Explore model governance, including building explainable, auditable, and interpretable machine learning models Use partial dependence plot, global feature summary, individual condition expectation, and feature interaction Build explainable models with global and local feature summary, and influence functions in practice Design and build explainable machine learning pipelines with transparency Discover Microsoft FairLearn and marketplace for different open-source explainable AI tools and cloud platforms Who this book is for This book is for data scientists, machine learning engineers, AI practitioners, IT professionals, business stakeholders, and AI ethicists who are responsible for implementing AI models in their organizations.

Ai And Ml For Coders In Pytorch

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Author : Laurence Moroney
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2025-06-30

Ai And Ml For Coders In Pytorch written by Laurence Moroney 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 2025-06-30 with Computers categories.

Eager to learn AI and machine learning but unsure where to start? Laurence Moroney's hands-on, code-first guide demystifies complex AI concepts without relying on advanced mathematics. Designed for programmers, it focuses on practical applications using PyTorch, helping you build real-world models without feeling overwhelmed. From computer vision and natural language processing (NLP) to generative AI with Hugging Face Transformers, this book equips you with the skills most in demand for AI development today. You'll also learn how to deploy your models across the web and cloud confidently. Gain the confidence to apply AI without needing advanced math or theory expertise Discover how to build AI models for computer vision, NLP, and sequence modeling with PyTorch Learn generative AI techniques with Hugging Face Diffusers and Transformers

Enterprise Ai In The Cloud

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Author : Rabi Jay
language : en
Publisher: John Wiley & Sons
Release Date : 2023-12-20

Enterprise Ai In The Cloud written by Rabi Jay and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Computers categories.

Embrace emerging AI trends and integrate your operations with cutting-edge solutions Enterprise AI in the Cloud: A Practical Guide to Deploying End-to-End Machine Learning and ChatGPT Solutions is an indispensable resource for professionals and companies who want to bring new AI technologies like generative AI, ChatGPT, and machine learning (ML) into their suite of cloud-based solutions. If you want to set up AI platforms in the cloud quickly and confidently and drive your business forward with the power of AI, this book is the ultimate go-to guide. The author shows you how to start an enterprise-wide AI transformation effort, taking you all the way through to implementation, with clearly defined processes, numerous examples, and hands-on exercises. You'll also discover best practices on optimizing cloud infrastructure for scalability and automation. Enterprise AI in the Cloud helps you gain a solid understanding of: AI-First Strategy: Adopt a comprehensive approach to implementing corporate AI systems in the cloud and at scale, using an AI-First strategy to drive innovation State-of-the-Art Use Cases: Learn from emerging AI/ML use cases, such as ChatGPT, VR/AR, blockchain, metaverse, hyper-automation, generative AI, transformer models, Keras, TensorFlow in the cloud, and quantum machine learning Platform Scalability and MLOps (ML Operations): Select the ideal cloud platform and adopt best practices on optimizing cloud infrastructure for scalability and automation AWS, Azure, Google ML: Understand the machine learning lifecycle, from framing problems to deploying models and beyond, leveraging the full power of Azure, AWS, and Google Cloud platforms AI-Driven Innovation Excellence: Get practical advice on identifying potential use cases, developing a winning AI strategy and portfolio, and driving an innovation culture Ethical and Trustworthy AI Mastery: Implement Responsible AI by avoiding common risks while maintaining transparency and ethics Scaling AI Enterprise-Wide: Scale your AI implementation using Strategic Change Management, AI Maturity Models, AI Center of Excellence, and AI Operating Model Whether you're a beginner or an experienced AI or MLOps engineer, business or technology leader, or an AI student or enthusiast, this comprehensive resource empowers you to confidently build and use AI models in production, bridging the gap between proof-of-concept projects and real-world AI deployments. With over 300 review questions, 50 hands-on exercises, templates, and hundreds of best practice tips to guide you through every step of the way, this book is a must-read for anyone seeking to accelerate AI transformation across their enterprise.

Enterprise Intelligence Building Scalable Data Products For The Digital Supply Chain 2025

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Author : Author 1 : NAVEEN SAIKRISHNA PUPPALA, Author 2 : MASTER DR. S. B. KISHOR
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :

Enterprise Intelligence Building Scalable Data Products For The Digital Supply Chain 2025 written by Author 1 : NAVEEN SAIKRISHNA PUPPALA, Author 2 : MASTER DR. S. B. KISHOR and has been published by YASHITA PRAKASHAN PRIVATE LIMITED this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.

PREFACE In today’s hyper-connected global economy, supply chains have evolved from linear, function-centric processes into complex, data-driven ecosystems. As enterprises strive to remain agile, resilient, and customer-centric, the ability to harness and operationalize vast quantities of supply-chain data has become a strategic imperative. Enterprise Intelligence: Building Scalable Data Products for the Digital Supply Chain is designed to guide practitioners, architects, and decision-makers through the journey of transforming raw data into actionable intelligence that fuels competitive advantage. Drawing upon both industry best practices and cutting-edge research, this book is organized into eleven interrelated chapters, each addressing a critical dimension of end-to-end data-product development: · Foundations of Enterprise Intelligence in the Supply Chain establishes the conceptual framework, defining key principles and illustrating how data products differ from traditional reporting and analytics. · Architecting Scalable Data Infrastructure delves into the technology stack storage, compute, and networking required to support high-volume, low-latency workflows. · Data Governance and Quality in Supply Chain Systems underscores the importance of trust, consistency, and compliance, presenting methodologies to measure and enforce data integrity. · Real-Time Data Ingestion and Processing Pipelines explores modern stream-processing architectures that enable timely insights and reactive decision-making. · AI and ML for Predictive Supply Chain Intelligence demonstrates how machine learning models can anticipate demand fluctuations, optimize routes, and reduce inventory costs. · Digital Twins and Simulation for Operational Optimization shows how virtual replicas of physical systems empower “what-if” analyses and continuous process improvement. · Intelligent Inventory and Demand Planning Systems focuses on advanced algorithms for balancing stock levels, minimizing stockouts, and adapting to shifting market conditions. · Supplier and Risk Intelligence Platforms examines frameworks for evaluating supplier performance, forecasting disruptions, and automating risk mitigation. · Orchestrating Data Products for Supply Chain Collaboration addresses the cultural and technical mechanisms needed to share insights across organizational boundaries. · Cloud-Native Integration with ERP and Logistics Systems guides readers through seamless connectivity with enterprise resource planning and transportation-management solutions. · Visual Analytics and Decision Intelligence Dashboards demonstrates how intuitive, interactive interfaces translate complex data into clear, decision-ready insights. Whether you are building your first data-product prototype or scaling a global analytics platform, this book offers both strategic guidance and hands-on techniques. Throughout, you will find real-world examples, illustrative diagrams, and practical checklists designed to accelerate adoption and drive measurable outcomes. It is our hope that by the end of this journey, you will possess the knowledge and confidence to architect, deploy, and govern data products that unlock the full potential of your digital supply chain. Authors Naveen Saikrishna Puppala Master Dr. S. B. Kishor

Software Engineering Research And Practice And E Learning E Business Enterprise Information Systems And E Government

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Author : Hamid R. Arabnia
language : en
Publisher: Springer Nature
Release Date : 2025-04-15

Software Engineering Research And Practice And E Learning E Business Enterprise Information Systems And E Government written by Hamid R. Arabnia and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-15 with Computers categories.

This book constitutes the proceedings of the 22nd International Conference on Software Engineering Research and Practice, SERP 2024, and the 23rd International Conference on e-Learning, e-Business, Enterprise Information Systems, and e-Government, EEE 2024, held as part of the 2024 World Congress in Computer Science, Computer Engineering and Applied Computing, in Las Vegas, USA, during July 22 to July 25, 2024. For SERP 2024, 52 submissions have been received and 9 papers have been accepted for publication in these proceedings; the 12 papers included from EEE 2024 have been carefully reviewed and selected from 55 submissions. They have been organized in topical sections as follows: software engineering research and practice; e-learning, e-business, enterprise information systems and e-government.

Agentic Ai In Enterprise

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Author : Sumit Ranjan
language : en
Publisher: Springer Nature
Release Date : 2025-08-13

Agentic Ai In Enterprise written by Sumit Ranjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-13 with Computers categories.

This book delves into the transformative power of Enterprise Agentic AI, tracing its evolution from basic automation to intelligent agents capable of contextual reasoning, memory retention, and autonomous decision-making. It provides a strategic roadmap for enterprises looking to integrate Agentic AI seamlessly into their operations while ensuring scalability, efficiency, and security. Readers will explore architectural best practices, including cloud, hybrid, and on-premises deployment models, and gain insights into LLM optimization strategies like Retrieval-Augmented Generation (RAG) and fine-tuning. The book also covers advanced prompt engineering techniques, the role of vector databases in AI-driven applications, and governance frameworks to ensure ethical, transparent, and responsible AI adoption. Through real-world case studies, the book illustrates AI’s impact across retail, healthcare, supply chain management, and customer engagement. It also examines the next wave of AI advancements, such as autonomous decision-making, AI-augmented leadership, and the evolving synergy between human expertise and intelligent agents in enterprise settings. By the end of this book, readers will have the knowledge and tools to design, deploy, and manage AI agents that are not only cutting-edge but also aligned with enterprise security, governance, and ethical standards. You Will: Understand how AI agents go beyond traditional models by incorporating contextual reasoning, long-term memory, and autonomous decision-making to enhance enterprise operations. Explore scalable deployment models (cloud, hybrid, on-premises) and best practices for integrating LLMs, vector databases, and prompt engineering into your AI workflows. Develop robust AI governance frameworks, conduct risk assessments, and implement security protocols to safeguard enterprise data while ensuring responsible AI adoption. Gain insights into transparency, accountability, and fairness in AI deployments, ensuring AI agents align with corporate values and global ethical standards. This book is for : Enterprise Architects.

Digital Image Processing Using Python

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Author : Dr. Manish Kashyap
language : en
Publisher: BPB Publications
Release Date : 2025-01-28

Digital Image Processing Using Python written by Dr. Manish Kashyap and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-28 with Computers categories.

DESCRIPTION “Digital Image Processing Using Python" offers a comprehensive guide to mastering image processing techniques through practical Python implementations. It equips you with the essential tools and knowledge to manipulate, analyze, and transform digital images using the powerful programming language, Python. This book offers a comprehensive exploration of digital image processing, combining theoretical foundations with practical applications. Starting with fundamental concepts like image representation and pixel neighborhoods, the book teaches Python programming and essential libraries for image manipulation. It covers a wide range of techniques, including spatial and frequency domain filtering, non-linear processing, noise reduction, wavelet transforms, and binary morphology. Advanced topics such as phase-based processing, multi-resolution analysis, and morphological operations are also explored in depth. The book provides practical examples and exercises to reinforce learning and equip readers with the skills needed to effectively process and analyze digital images for various applications. By integrating Python code with visual examples, you will gain practical experience and insights that are directly applicable to your work. This approach ensures that you not only learn theoretical concepts but also understand how to implement them effectively in real-world situations. KEY FEATURES ● Builds a strong foundation in digital image processing, covering essential topics from basics to advanced techniques. ● Includes practical exercises to master Python programming and essential libraries like OpenCV and NumPy for image manipulation tasks. ● Applies concepts to real-world scenarios like image restoration, object detection, and medical imaging. WHAT YOU WILL LEARN ● Implement image processing techniques using Python libraries and tools. ● Understand core concepts like filtering, segmentation, and enhancement. ● Apply practical Python code to real-world image processing tasks. ● Develop skills to analyze and manipulate digital images effectively. ● Create and visualize image processing algorithms with hands-on examples. WHO THIS BOOK IS FOR This book is perfect for undergraduate and master's level students seeking to grasp image processing concepts or professionals working in fields like computer vision, artificial intelligence, or medical imaging. TABLE OF CONTENTS 1. Introduction to Digital Images 2. Python Fundamentals and Related Libraries 3. Playing with Digital Images 4. Spatial Domain Processing 5. Frequency Domain Image Processing 6. Non-linear Image Processing and the Issue of Phase 7. Noise and Image Restoration 8. Wavelet Transform and Multi-resolution Analysis 9. Binary Morphology

Enterprise Architecture In The Age Of A I

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Author : Ian Loe
language : en
Publisher: Ian Loe
Release Date : 2024-09-17

Enterprise Architecture In The Age Of A I written by Ian Loe and has been published by Ian Loe this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-17 with Computers categories.

"Enterprise Architecture in the Age of AI: Challenges and Opportunities" is a strategic guide that explores how Artificial Intelligence (AI) is transforming Enterprise Architecture (EA) to create smarter, more agile, and data-driven organisations. The book provides an overview of AI’s impact on EA frameworks, roles, and responsibilities, offering insights into building AI-ready architectures, integrating AI with existing systems, and leveraging AI for enhanced decision-making and automation. It addresses the opportunities and challenges of AI-driven EA, including AI governance, ethics, and risk management, and presents a suggested roadmap for AI integration. Ideal for enterprise architects, IT leaders, and digital transformation professionals, this book equips readers with the knowledge and tools needed to harness AI to drive innovation in a rapidly evolving digital landscape.

The Artificial Intelligence And Machine Learning Blueprint Foundations Frameworks And Real World Applications

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Author : Priyambada Swain
language : en
Publisher: Deep Science Publishing
Release Date : 2025-08-06

The Artificial Intelligence And Machine Learning Blueprint Foundations Frameworks And Real World Applications written by Priyambada Swain and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-06 with Computers categories.

In the current era of data-centric transformation, Artificial Intelligence (AI) and Machine Learning (ML) are influencing organizational strategies and operations. The AI and Machine Learning Blueprint serves as a guide connecting academic concepts with industry applications. It is intended for both students seeking basic knowledge and professionals interested in deploying scalable AI systems. The book covers core mathematical principles relevant to AI, including linear algebra, probability, statistics, and optimization, and provides an overview of classical machine learning algorithms, neural networks, and reinforcement learning. Concepts are illustrated with practical examples, Python code, and case studies from sectors such as healthcare, finance, cybersecurity, natural language processing, and computer vision. Operational considerations are also addressed, with chapters on MLOps, model deployment, explainable AI (XAI), and ethics. The text concludes with information on emerging topics including generative AI, federated learning, and artificial general intelligence (AGI). With a blend of theoretical depth and practical relevance, this book is an essential blueprint for mastering AI and ML in today’s intelligent systems landscape.