Cloud Based Machine Learning Practical Guide To Deploying Ai Models In The Cloud
DOWNLOAD
Download Cloud Based Machine Learning Practical Guide To Deploying Ai Models In The Cloud PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Cloud Based Machine Learning Practical Guide To Deploying Ai Models In The Cloud book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Cloud Based Machine Learning Practical Guide To Deploying Ai Models In The Cloud
DOWNLOAD
Author : Hemanth Volikatla
language : en
Publisher: RK Publication
Release Date : 2024-05-15
Cloud Based Machine Learning Practical Guide To Deploying Ai Models In The Cloud written by Hemanth Volikatla and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-15 with Computers categories.
Cloud-Based Machine Learning – Practical Guide to Deploying AI Models in the Cloud is a comprehensive resource designed to help professionals and enthusiasts harness the power of cloud platforms for AI deployment. It's key concepts, tools, and techniques for building, training, and deploying machine learning models using services like AWS, Azure, and Google Cloud. With practical examples, step-by-step instructions, and best practices, this guide empowers readers to scale AI solutions efficiently, ensuring robust performance and seamless integration into real-world applications. Perfect for beginners and experts aiming to advance their skills in cloud-based AI technologies.
Pragmatic Ai
DOWNLOAD
Author : Noah Gift
language : en
Publisher: Addison-Wesley Professional
Release Date : 2018-07-12
Pragmatic Ai written by Noah Gift and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-07-12 with Computers categories.
Master Powerful Off-the-Shelf Business Solutions for AI and Machine Learning Pragmatic AI will help you solve real-world problems with contemporary machine learning, artificial intelligence, and cloud computing tools. Noah Gift demystifies all the concepts and tools you need to get results—even if you don’t have a strong background in math or data science. Gift illuminates powerful off-the-shelf cloud offerings from Amazon, Google, and Microsoft, and demonstrates proven techniques using the Python data science ecosystem. His workflows and examples help you streamline and simplify every step, from deployment to production, and build exceptionally scalable solutions. As you learn how machine language (ML) solutions work, you’ll gain a more intuitive understanding of what you can achieve with them and how to maximize their value. Building on these fundamentals, you’ll walk step-by-step through building cloud-based AI/ML applications to address realistic issues in sports marketing, project management, product pricing, real estate, and beyond. Whether you’re a business professional, decision-maker, student, or programmer, Gift’s expert guidance and wide-ranging case studies will prepare you to solve data science problems in virtually any environment. Get and configure all the tools you’ll need Quickly review all the Python you need to start building machine learning applications Master the AI and ML toolchain and project lifecycle Work with Python data science tools such as IPython, Pandas, Numpy, Juypter Notebook, and Sklearn Incorporate a pragmatic feedback loop that continually improves the efficiency of your workflows and systems Develop cloud AI solutions with Google Cloud Platform, including TPU, Colaboratory, and Datalab services Define Amazon Web Services cloud AI workflows, including spot instances, code pipelines, boto, and more Work with Microsoft Azure AI APIs Walk through building six real-world AI applications, from start to finish Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Data Engineering On The Cloud A Practical Guide 2025
DOWNLOAD
Author : Raghu Gopa, Dr. Arpita Roy
language : en
Publisher: YASHITA PRAKASHAN PRIVATE LIMITED
Release Date :
Data Engineering On The Cloud A Practical Guide 2025 written by Raghu Gopa, Dr. Arpita Roy 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 The digital transformation of businesses and the exponential growth of data have created a fundamental shift in how organizations approach data management, analytics, and decision-making. As cloud technologies continue to evolve, cloud-based data engineering has become central to the success of modern data-driven enterprises. “Data Engineering on the Cloud: A Practical Guide” aims to equip data professionals, engineers, and organizations with the knowledge and practical tools needed to build and manage scalable, secure, and efficient data engineering pipelines in cloud environments. This book is designed to bridge the gap between the theoretical foundations of data engineering and the practical realities of working with cloud-based data platforms. Cloud computing has revolutionized data storage, processing, and analytics by offering unparalleled scalability, flexibility, and cost efficiency. However, with these opportunities come new challenges, including selecting the right tools, architectures, and strategies to ensure seamless data integration, transformation, and delivery. As businesses increasingly migrate their data to the cloud, it is essential for data engineers to understand how to leverage the capabilities of the cloud to build robust data pipelines that can handle large, complex datasets in real-time. Throughout this guide, we will explore the various facets of cloud-based data engineering, from understanding cloud storage and computing services to implementing data integration techniques, managing data quality, and optimizing performance. Whether you are building data pipelines from scratch, migrating on-premises systems to the cloud, or enhancing existing data workflows, this book will provide actionable insights and step-by-step guidance on best practices, tools, and frameworks commonly used in cloud data engineering. Key topics covered in this book include: · The fundamentals of cloud architecture and the role of cloud providers (such as AWS, Google Cloud, and Microsoft Azure) in data engineering workflows. · Designing scalable and efficient data pipelines using cloud-based tools and services. · Integrating diverse data sources, including structured, semi-structured, and unstructured data, for seamless processing and analysis. · Data transformation techniques, including ETL (Extract, Transform, Load) and ELT (Extract, Load, Transform), in cloud environments. · Ensuring data quality, governance, and security when working with cloud data platforms. · Optimizing performance for data storage, processing, and analytics to handle growing data volumes and complexity. This book is aimed at professionals who are already familiar with data engineering concepts and are looking to apply those concepts within cloud environments. It is also suitable for organizations that are in the process of migrating to cloud-based data platforms and wish to understand the nuances and best practices for cloud data engineering. In addition to theoretical knowledge, this guide emphasizes hands-on approaches, providing practical examples, code snippets, and real-world case studies to demonstrate the effective implementation of cloud-based data engineering solutions. We will explore how to utilize cloud-native services to streamline workflows, improve automation, and reduce manual interventions in data pipelines. Throughout the book, you will gain insights into the evolving tools and technologies that make data engineering more agile, reliable, and efficient. The role of data engineering is growing ever more important in enabling businesses to unlock the value of their data. By the end of this book, you will have a comprehensive understanding of how to leverage cloud technologies to build high-performance, scalable data engineering solutions that are aligned with the needs of modern data-driven organizations. We hope this guide helps you to navigate the complexities of cloud data engineering and helps you unlock new possibilities for your data initiatives. Welcome to “Data Engineering on the Cloud: A Practical Guide.” Let’s embark on this journey to harness the full potential of cloud technologies in the world of data engineering. Authors
Building Machine Learning And Deep Learning Models On Google Cloud Platform
DOWNLOAD
Author : Ekaba Bisong
language : en
Publisher:
Release Date : 2019
Building Machine Learning And Deep Learning Models On Google Cloud Platform written by Ekaba Bisong and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Cloud computing categories.
Take a systematic approach to understanding the fundamentals of machine learning and deep learning from the ground up and how they are applied in practice. You will use this comprehensive guide for building and deploying learning models to address complex use cases while leveraging the computational resources of Google Cloud Platform. Author Ekaba Bisong shows you how machine learning tools and techniques are used to predict or classify events based on a set of interactions between variables known as features or attributes in a particular dataset. He teaches you how deep learning extends the machine learning algorithm of neural networks to learn complex tasks that are difficult for computers to perform, such as recognizing faces and understanding languages. And you will know how to leverage cloud computing to accelerate data science and machine learning deployments. Building Machine Learning and Deep Learning Models on Google Cloud Platform is divided into eight parts that cover the fundamentals of machine learning and deep learning, the concept of data science and cloud services, programming for data science using the Python stack, Google Cloud Platform (GCP) infrastructure and products, advanced analytics on GCP, and deploying end-to-end machine learning solution pipelines on GCP. You will: Understand the principles and fundamentals of machine learning and deep learning, the algorithms, how to use them, when to use them, and how to interpret your results Know the programming concepts relevant to machine and deep learning design and development using the Python stack Build and interpret machine and deep learning models Use Google Cloud Platform tools and services to develop and deploy large-scale machine learning and deep learning products Be aware of the different facets and design choices to consider when modeling a learning problem Productionalize machine learning models into software products.
A Practical Guide To Generative Ai Using Amazon Bedrock
DOWNLOAD
Author : Avik Bhattacharjee
language : en
Publisher: Springer Nature
Release Date : 2025-07-08
A Practical Guide To Generative Ai Using Amazon Bedrock written by Avik Bhattacharjee and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-08 with Computers categories.
This comprehensive guide gives you the knowledge and skills you need to excel in Generative AI. From understanding the fundamentals to mastering techniques, this book offers a step-by-step approach to leverage Amazon Bedrock to build, deploy, and secure Generative AI applications. The book presents structured chapters and practical examples to delve into key concepts such as prompt engineering, retrieval-augmented generation, and model evaluation. You will gain profound insights into the Amazon Bedrock platform. The book covers setup, life cycle management, and integration with Amazon SageMaker. The book emphasizes real-world applications, and provides use cases and best practices across industries on topics such as text summarization, image generation, and conversational AI bots. The book tackles vital topics including data privacy, security, responsible AI practices, and guidance on navigating governance and monitoring challenges while ensuring adherence to ethical standards and regulations. The book provides the tools and knowledge needed to excel in the rapidly evolving field of Generative AI. Whether you're a data scientist, AI engineer, or business professional, this book will empower you to harness the full potential of Generative AI and drive innovation in your organization. What You Will Learn Understand the fundamentals of Generative AI and Amazon Bedrock Build Responsible Generative AI applications leveraging Amazon Bedrock Know techniques and best practices See real-world applications Integrate and manage platforms Handle securty and governance issues Evaluate and optimze models Gain future-ready insights Understand the project life cycle when building Generative AI Applications Who This Book Is For Data scientistys, AI/ML engineers and architects, software developers plus AI enthusiasts and studenta and educators, and leaders who want to evangelize within organizatios
Generative Ai For Beginners Practical Guide To Chatgpt Machine Learning And Ai Applications
DOWNLOAD
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.
Practical Deep Learning For Cloud Mobile And Edge
DOWNLOAD
Author : Anirudh Koul
language : en
Publisher: O'Reilly Media
Release Date : 2019-10-14
Practical Deep Learning For Cloud Mobile And Edge written by Anirudh Koul 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 2019-10-14 with Computers categories.
Whether you’re a software engineer aspiring to enter the world of deep learning, a veteran data scientist, or a hobbyist with a simple dream of making the next viral AI app, you might have wondered where to begin. This step-by-step guide teaches you how to build practical deep learning applications for the cloud, mobile, browsers, and edge devices using a hands-on approach. Relying on years of industry experience transforming deep learning research into award-winning applications, Anirudh Koul, Siddha Ganju, and Meher Kasam guide you through the process of converting an idea into something that people in the real world can use. Train, tune, and deploy computer vision models with Keras, TensorFlow, Core ML, and TensorFlow Lite Develop AI for a range of devices including Raspberry Pi, Jetson Nano, and Google Coral Explore fun projects, from Silicon Valley’s Not Hotdog app to 40+ industry case studies Simulate an autonomous car in a video game environment and build a miniature version with reinforcement learning Use transfer learning to train models in minutes Discover 50+ practical tips for maximizing model accuracy and speed, debugging, and scaling to millions of users
Deep Learning For Coders With Fastai And Pytorch
DOWNLOAD
Author : Jeremy Howard
language : en
Publisher: O'Reilly Media
Release Date : 2020-06-29
Deep Learning For Coders With Fastai And Pytorch written by Jeremy Howard 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 2020-06-29 with Computers categories.
Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala
Advanced Analytics And Machine Learning For Business Growth A Practical Guide
DOWNLOAD
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
Python Power A Practical Guide To Programming Through Hands On Projects
DOWNLOAD
Author : Jefferey Rangel
language : en
Publisher: Lena Whitmore
Release Date : 2025-04-04
Python Power A Practical Guide To Programming Through Hands On Projects written by Jefferey Rangel and has been published by Lena Whitmore this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-04 with Computers categories.
Are you ready to unlock the power of Python? This book is your comprehensive guide to mastering this versatile programming language, from beginner to confident coder. Dive into the fundamentals of Python, learning essential concepts like variables, data types, operators, and control flow. You'll build a strong foundation by working through clear explanations and interactive code examples. The focus is on practical application, so you'll learn by doing, tackling real-world projects that will solidify your understanding. This book caters to anyone eager to learn Python, whether you're a complete novice or have some prior coding experience. No matter your background, you'll find the clear and concise instructions, engaging examples, and hands-on projects perfectly tailored to your learning style. This book is more than just theory; it's your launchpad for coding success. You'll learn to write clean and efficient code, solve problems creatively, and build impressive projects. With each project, your confidence and programming skills will grow. Invest in this book and unlock your potential in the world of Python programming.