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Authors: Christoffer Noring (2024) - AI-Assisted Programming for Web and Machine Learning shows you how to build applications and machine learning models and automate repetitive tasks. Part 1 focuses on coding, from building a user interface to the backend. You’ll use prompts to create the appearance of an app using HTML, styling with CSS, adding behavior with JavaScript, and working with multiple viewports. Next, you’ll build a web API with Python and Flask and refactor the code to improve code readability. Part 1 ends with using GitHub Copilot to improve the maintainability and performance of existing code. Part 2 provides a prompting toolkit for data science from data checking (inspecting data and creating distribution graphs and correlation matrices) to building and optimizing a neural network. You’ll use different...
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Authors: K. Ganesh (2014) - This book introduces the fundamental principles of understanding business requirements to apply enterprise resource planning (ERP) in order to meet business needs. The book also helps readers understand the usage of ERP for monitoring and controlling business processes, while providing practical oriented solutions to the design and implementation of ERP. Using the provided framework, a business can decide to provide more value at lower cost which increases its competitive advantage. This should be an ideal reference for executives, researchers and consultants in project management of ERP. ERP can be considered to be an integrated package of business process.
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Authors: Maxim Lapan (2020) - Second Edition is an updated and expanded version of the bestselling guide to the very latest reinforcement learning (RL) tools and techniques. It provides you with an introduction to the fundamentals of RL, along with the hands-on ability to code intelligent learning agents to perform a range of practical tasks.
With six new chapters devoted to a variety of up-to-the-minute developments in RL, including discrete optimization (solving the Rubik's Cube), multi-agent methods, Microsoft's TextWorld environment, advanced exploration techniques, and more, you will come away from this book with a deep understanding of the latest innovations in this emerging field.
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Authors: Sanjay Kumar Biswash (2021) - This book provides a framework for the next generation of cloud networks, which is the emerging part of 5G partnership projects. This contributed book has following salient features, A cloud-based next generation networking technologies. Cloud-based IoT and mobility management technology. The proposed book is a reference for research scholars and course supplement for cloud-IoT related subjects such as distributed networks in computer/ electrical engineering.
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Authors: Roberto Zagni (2023) - This book begins by introducing you to dbt and its role in the data stack, along with how it uses simple SQL to build your data platform, helping you and your team work better together. You'll find out how to leverage data modeling, data quality, master data management, and more to build a simple-to-understand and future-proof solution. As you advance, you'll explore the modern data stack, understand how data-related careers are changing, and see how dbt enables this transition into the emerging role of an analytics engineer.
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Authors: Kai Hwang (2012) - Complete coverage of modern distributed computing technology including clusters, the grid, service-oriented architecture, massively parallel processors, peer-to-peer networking, and cloud computing. Includes case studies from the leading distributed computing vendors: Amazon, Microsoft, Google, and more. Explains how to use virtualization to facilitate management, debugging, migration, and disaster recovery. Designed for undergraduate or graduate students taking a distributed systems course―each chapter includes exercises and further reading, with lecture slides and more available online
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Authors: Karl Kurbel (2013) - This book is about running modern industrial enterprises with the help of information systems.Enterprise resource planning (ERP) is the core of business information processing. An ERP system is the backbone of most companies' information systems landscape. All major business processes are handled with the help of this system.
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Authors: Hien Luu (2021) - In this book, you will gain expertise on the powerful and efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing data in batch and streaming; and the scalable machine learning algorithms and practical utilities to build machine learning applications. Beginning Apache Spark 3 begins by explaining different ways of interacting with Apache Spark, such as Spark Concepts and Architecture, and Spark Unified Stack.
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Authors: Sandeep Bhowmik (2017) - This textbook is ideal for undergraduate and graduate students of computer science engineering, and information technology.Presents in-depth coverage on fundamental concepts and essential technologies of cloud computing. Emphasizes popular cloud services and security issues. Contains case studies and emerging trends including internet of things Includes numerous review questions and multiple choice questions for better understanding.
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Authors: Nitin Jaglal Untwal (2025) - In this book, you'll discover how to harness the latest data analytics techniques, including machine learning and inferential statistics, to make informed investment decisions and drive business success. With a focus on practical application, this book takes you on a journey from the basics of data preprocessing and visualization to advanced modeling techniques for stock price prediction.
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