Practical Guide To H2o Ai
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Practical Guide To H2o Ai
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Author : Richard Johnson
language : en
Publisher: HiTeX Press
Release Date : 2025-05-31
Practical Guide To H2o Ai written by Richard Johnson and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-31 with Computers categories.
"Practical Guide to H2O.ai" "Practical Guide to H2O.ai" is a comprehensive resource designed for data scientists, machine learning engineers, and IT professionals who seek to master the full capabilities of H2O.ai’s powerful platform. This guide delivers a deep dive into the architecture and components of the H2O ecosystem—including H2O-3 and Driverless AI—while demystifying its integration within diverse enterprise environments, whether on-premises, cloud, or hybrid. Readers will gain actionable insights into secure system deployment, cluster management, large-scale data ingestion, and optimized ETL workflows, ensuring robust infrastructure that meets the demands of modern data-driven organizations. Structured to support both practical adoption and technical excellence, the book traverses core machine learning tasks, from advanced preprocessing and feature engineering to supervised and unsupervised learning with leading algorithms such as GBM, XGBoost, and deep neural networks. Special emphasis is placed on scalable automation through H2O AutoML, presenting real-world case studies while showcasing best practices in algorithm selection, hyperparameter optimization, and model evaluation. Dedicated chapters explore explainable AI and responsible ML practices—covering interpretability, bias mitigation, compliance, and data privacy—empowering readers to build transparent, auditable, and trustworthy solutions for complex, regulated domains. With detailed coverage of emerging fields like natural language processing, time series analysis, MLOps, and distributed deep learning, "Practical Guide to H2O.ai" is an indispensable reference for leveraging H2O.ai at scale. Topics such as advanced model deployment, real-time inference, CI/CD integration, and production troubleshooting combine theory with hands-on strategies for operationalizing machine learning workflows. Whether you are scaling to petabyte data, orchestrating containerized clusters, or exploring cutting-edge areas like federated learning and edge ML, this guide equips you with the knowledge and tools to drive innovation and achieve enterprise-level AI success.
Machine Learning At Scale With H2o
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Author : Gregory Keys
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-07-29
Machine Learning At Scale With H2o written by Gregory Keys 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 2022-07-29 with Computers categories.
Build predictive models using large data volumes and deploy them to production using cutting-edge techniques Key Features • Build highly accurate state-of-the-art machine learning models against large-scale data • Deploy models for batch, real-time, and streaming data in a wide variety of target production systems • Explore all the new features of the H2O AI Cloud end-to-end machine learning platform Book Description H2O is an open source, fast, and scalable machine learning framework that allows you to build models using big data and then easily productionalize them in diverse enterprise environments. Machine Learning at Scale with H2O begins with an overview of the challenges faced in building machine learning models on large enterprise systems, and then addresses how H2O helps you to overcome them. You'll start by exploring H2O's in-memory distributed architecture and find out how it enables you to build highly accurate and explainable models on massive datasets using your favorite ML algorithms, language, and IDE. You'll also get to grips with the seamless integration of H2O model building and deployment with Spark using H2O Sparkling Water. You'll then learn how to easily deploy models with H2O MOJO. Next, the book shows you how H2O Enterprise Steam handles admin configurations and user management, and then helps you to identify different stakeholder perspectives that a data scientist must understand in order to succeed in an enterprise setting. Finally, you'll be introduced to the H2O AI Cloud platform and explore the entire machine learning life cycle using multiple advanced AI capabilities. By the end of this book, you'll be able to build and deploy advanced, state-of-the-art machine learning models for your business needs. What you will learn • Build and deploy machine learning models using H2O • Explore advanced model-building techniques • Integrate Spark and H2O code using H2O Sparkling Water • Launch self-service model building environments • Deploy H2O models in a variety of target systems and scoring contexts • Expand your machine learning capabilities on the H2O AI Cloud Who this book is for This book is for data scientists and machine learning engineers who want to gain hands-on machine learning experience by building and deploying state-of-the-art models with advanced techniques using H2O technology. An understanding of the data science process and experience in Python programming is recommended. This book will also benefit students by helping them understand how machine learning works in real-world enterprise scenarios.
Advanced Analytics And Machine Learning For Business Growth A Practical Guide
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Author : Vybhav Reddy Kammireddy Changalreddy Prof Ashok Kumar
language : en
Publisher: DeepMisti Publication
Release Date : 2025-01-15
Advanced Analytics And Machine Learning For Business Growth A Practical Guide written by Vybhav Reddy Kammireddy Changalreddy Prof Ashok Kumar and has been published by DeepMisti Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-15 with Computers categories.
In today’s competitive business landscape, growth is no longer just about hard work and intuition—it’s about making smarter decisions driven by insights from data. The advent of advanced analytics and machine learning (ML) has revolutionized how businesses understand their markets, optimize operations, and delight customers. Yet, the journey from raw data to actionable insights can be daunting, especially for organizations new to these transformative technologies. Advanced Analytics and Machine Learning for Business Growth: A Practical Guide is designed to demystify the complex world of analytics and machine learning, providing business leaders, analysts, and data enthusiasts with a clear and actionable roadmap to drive tangible results. This book bridges the gap between the technical depth of data science and the practical demands of business strategy, empowering readers to unlock the full potential of their data. Inside, you’ll discover: • The foundational principles of advanced analytics and machine learning in business contexts. • Practical applications for solving real-world challenges such as customer segmentation, churn prediction, and demand forecasting. • Step-by-step guides for implementing machine learning models, from data preparation to deployment. • Tools, platforms, and frameworks that accelerate analytics workflows. • Insights into navigating challenges like data quality, organizational buy-in, and ethical AI practices. This book is intentionally practical. Instead of overwhelming you with complex theories and algorithms, it focuses on actionable strategies that you can implement immediately, whether you’re working in retail, finance, healthcare, manufacturing, or any other industry. As you turn the pages, you’ll discover how advanced analytics and machine learning can transform your business—from identifying hidden opportunities to solving critical challenges. More importantly, you’ll gain the confidence to lead data-driven initiatives that foster growth, resilience, and competitive advantage. The future belongs to businesses that can adapt and innovate. With this book as your guide, you’re equipped to harness the power of advanced analytics and machine learning to fuel your organization’s growth and success. Welcome to the journey of transforming your business with data. Let’s build the future, one insight at a time. Authors
Disruptive Analytics
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Author : Thomas W. Dinsmore
language : en
Publisher: Apress
Release Date : 2016-08-27
Disruptive Analytics written by Thomas W. Dinsmore and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-08-27 with Computers categories.
Learn all you need to know about seven key innovations disrupting business analytics today. These innovations—the open source business model, cloud analytics, the Hadoop ecosystem, Spark and in-memory analytics, streaming analytics, Deep Learning, and self-service analytics—are radically changing how businesses use data for competitive advantage. Taken together, they are disrupting the business analytics value chain, creating new opportunities. Enterprises who seize the opportunity will thrive and prosper, while others struggle and decline: disrupt or be disrupted. Disruptive Business Analytics provides strategies to profit from disruption. It shows you how to organize for insight, build and provision an open source stack, how to practice lean data warehousing, and how to assimilate disruptive innovations into an organization. Through a short history of business analytics and a detailed survey of products and services, analytics authority Thomas W. Dinsmore provides a practical explanation of the most compelling innovations available today. What You'll Learn Discover how the open source business model works and how to make it work for you See how cloud computing completely changes the economics of analytics Harness the power of Hadoop and its ecosystem Find out why Apache Spark is everywhere Discover the potential of streaming and real-time analytics Learn what Deep Learning can do and why it matters See how self-service analytics can change the way organizations do business Who This Book Is For Corporate actors at all levels of responsibility for analytics: analysts, CIOs, CTOs, strategic decision makers, managers, systems architects, technical marketers, product developers, IT personnel, and consultants.
Machine Learning For High Risk Applications
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Author : Patrick Hall
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-04-17
Machine Learning For High Risk Applications written by Patrick Hall 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 2023-04-17 with Computers categories.
The past decade has witnessed the broad adoption of artificial intelligence and machine learning (AI/ML) technologies. However, a lack of oversight in their widespread implementation has resulted in some incidents and harmful outcomes that could have been avoided with proper risk management. Before we can realize AI/ML's true benefit, practitioners must understand how to mitigate its risks. This book describes approaches to responsible AI—a holistic framework for improving AI/ML technology, business processes, and cultural competencies that builds on best practices in risk management, cybersecurity, data privacy, and applied social science. Authors Patrick Hall, James Curtis, and Parul Pandey created this guide for data scientists who want to improve real-world AI/ML system outcomes for organizations, consumers, and the public. Learn technical approaches for responsible AI across explainability, model validation and debugging, bias management, data privacy, and ML security Learn how to create a successful and impactful AI risk management practice Get a basic guide to existing standards, laws, and assessments for adopting AI technologies, including the new NIST AI Risk Management Framework Engage with interactive resources on GitHub and Colab
Generative Ai For Beginners Practical Guide To Chatgpt Machine Learning And Ai Applications
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Author : Caleb Morgan Whitaker
language : en
Publisher: Gabriel Mensah
Release Date : 2025-07-07
Generative Ai For Beginners Practical Guide To Chatgpt Machine Learning And Ai Applications written by Caleb Morgan Whitaker and has been published by Gabriel Mensah this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-07 with Computers categories.
🤖 Learn Generative AI — From Zero to Real Projects with Confidence Curious about AI but overwhelmed by technical jargon? Generative AI for Beginners is your clear, hands‑on guide to mastering ChatGPT, neural networks, and practical AI applications—all explained in simple terms for non‑techies and aspiring creators. 🔍 What You’ll Learn & Build Generative AI Simplified Explore how models like GPT‑4, GANs, and VAEs generate text, images, and audio—without getting lost in mathematics. Source: Generative AI for Beginners: A Comprehensive Guide simplifies these concepts for novices. ChatGPT & Prompt Engineering Learn how to design prompts that elicit useful, high‑quality responses for writing, decision‑making, or brainstorming—just like top-rated beginner AI guides. Neural Networks Made Accessible Cover core machine learning ideas like backpropagation, supervised vs. unsupervised learning, and model training using intuitive, non-technical explanations . Practical AI Applications You Can Build Use guided mini‑projects—create a chatbot, prompt‑powered text generator, or image generator—using free and open‑source tools, and gain real hands‑on experience. Ethics & Future Opportunities Understand ethical considerations, bias issues, and emerging Web3/AI trends so you can build responsibly and stay ahead . 🎯 Why This Book Works Beginner-First, Jargon-Free – No prior experience required. Learn at your own pace, with bite‑sized chapters. Project-Based Learning – Each section builds a real AI tool, not just theory—similar to bestsellers that focus on application. Up‑to‑Date for 2025 – Covers current models like GPT‑4, open-source frameworks like Hugging Face, and modern AI applications. Balance of Theory & Practice – Unlike superficial overviews, this guide gives you both understanding and the means to create tangible AI projects. 💡 Your Gains in Action ✅Benefit. 🔥You’ll Be Able To… Understand AI Fundamentals. Clearly explain and use generative AI in daily tasks. Interact Smart with ChatGPT. Create prompts for writing, research, and business needs. Build Real Tools. Deploy your own chatbot, image generator, or text app. Upload & Use Ethical AI. Consider bias, consent, and best practices in your projects. Stay Ahead in AI Trends. Understand LLMs, neural nets, GANs, and future AI paths. 👤 Who Should Read This Beginners eager to start building AI without coding Professionals and students wanting a full AI foundation and skills Creatives and entrepreneurs looking to leverage AI tools in their projects Ready to build useful AI projects in real-time? Tap Add to Cart for Generative AI for Beginners—your step-by-step roadmap to mastering prompt engineering, neural networks, and real-world AI applications by just reading and doing.
Proceedings Of Sixth International Congress On Information And Communication Technology
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Author : Xin-She Yang
language : en
Publisher: Springer Nature
Release Date : 2021-09-23
Proceedings Of Sixth International Congress On Information And Communication Technology written by Xin-She Yang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-23 with Technology & Engineering categories.
This book gathers selected high-quality research papers presented at the Sixth International Congress on Information and Communication Technology, held at Brunel University, London, on February 25–26, 2021. It discusses emerging topics pertaining to information and communication technology (ICT) for managerial applications, e-governance, e-agriculture, e-education and computing technologies, the Internet of things (IoT) and e-mining. Written by respected experts and researchers working on ICT, the book offers a valuable asset for young researchers involved in advanced studies. The book is presented in four volumes.
Codeless Time Series Analysis With Knime
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Author : Corey Weisinger
language : en
Publisher: Packt Publishing Ltd
Release Date : 2022-08-19
Codeless Time Series Analysis With Knime written by Corey Weisinger 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 2022-08-19 with Computers categories.
Perform time series analysis using KNIME Analytics Platform, covering both statistical methods and machine learning-based methods Key Features • Gain a solid understanding of time series analysis and its applications using KNIME • Learn how to apply popular statistical and machine learning time series analysis techniques • Integrate other tools such as Spark, H2O, and Keras with KNIME within the same application Book Description This book will take you on a practical journey, teaching you how to implement solutions for many use cases involving time series analysis techniques. This learning journey is organized in a crescendo of difficulty, starting from the easiest yet effective techniques applied to weather forecasting, then introducing ARIMA and its variations, moving on to machine learning for audio signal classification, training deep learning architectures to predict glucose levels and electrical energy demand, and ending with an approach to anomaly detection in IoT. There's no time series analysis book without a solution for stock price predictions and you'll find this use case at the end of the book, together with a few more demand prediction use cases that rely on the integration of KNIME Analytics Platform and other external tools. By the end of this time series book, you'll have learned about popular time series analysis techniques and algorithms, KNIME Analytics Platform, its time series extension, and how to apply both to common use cases. What you will learn • Install and configure KNIME time series integration • Implement common preprocessing techniques before analyzing data • Visualize and display time series data in the form of plots and graphs • Separate time series data into trends, seasonality, and residuals • Train and deploy FFNN and LSTM to perform predictive analysis • Use multivariate analysis by enabling GPU training for neural networks • Train and deploy an ML-based forecasting model using Spark and H2O Who this book is for This book is for data analysts and data scientists who want to develop forecasting applications on time series data. While no coding skills are required thanks to the codeless implementation of the examples, basic knowledge of KNIME Analytics Platform is assumed. The first part of the book targets beginners in time series analysis, and the subsequent parts of the book challenge both beginners as well as advanced users by introducing real-world time series applications.
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.
Machine Learning And Big Data
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Author : Uma N. Dulhare
language : en
Publisher: John Wiley & Sons
Release Date : 2020-09-01
Machine Learning And Big Data written by Uma N. Dulhare 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 2020-09-01 with Computers categories.
This book is intended for academic and industrial developers, exploring and developing applications in the area of big data and machine learning, including those that are solving technology requirements, evaluation of methodology advances and algorithm demonstrations. The intent of this book is to provide awareness of algorithms used for machine learning and big data in the academic and professional community. The 17 chapters are divided into 5 sections: Theoretical Fundamentals; Big Data and Pattern Recognition; Machine Learning: Algorithms & Applications; Machine Learning's Next Frontier and Hands-On and Case Study. While it dwells on the foundations of machine learning and big data as a part of analytics, it also focuses on contemporary topics for research and development. In this regard, the book covers machine learning algorithms and their modern applications in developing automated systems. Subjects covered in detail include: Mathematical foundations of machine learning with various examples. An empirical study of supervised learning algorithms like Naïve Bayes, KNN and semi-supervised learning algorithms viz. S3VM, Graph-Based, Multiview. Precise study on unsupervised learning algorithms like GMM, K-mean clustering, Dritchlet process mixture model, X-means and Reinforcement learning algorithm with Q learning, R learning, TD learning, SARSA Learning, and so forth. Hands-on machine leaning open source tools viz. Apache Mahout, H2O. Case studies for readers to analyze the prescribed cases and present their solutions or interpretations with intrusion detection in MANETS using machine learning. Showcase on novel user-cases: Implications of Electronic Governance as well as Pragmatic Study of BD/ML technologies for agriculture, healthcare, social media, industry, banking, insurance and so on.