Uczenie maszynowe

MATLAB for Machine Learning. Practical examples of regression, clustering and neural networks

Giuseppe Ciaburro

MATLAB is the language of choice for many researchers and mathematics experts for machine learning. This book will help you build a foundation in machine learning using MATLAB for beginners.You’ll start by getting your system ready with t he MATLAB environment for machine learning and you’ll see how to easily interact with the Matlab workspace. We’ll then move on to data cleansing, mining and analyzing various data types in machine learning and you’ll see how to display data values on a plot. Next, you’ll get to know about the different types of regression techniques and how to apply them to your data using the MATLAB functions. You’ll understand the basic concepts of neural networks and perform data fitting, pattern recognition, and clustering analysis. Finally, you’ll explore feature selection and extraction techniques for dimensionality reduction for performance improvement. At the end of the book, you will learn to put it all together into real-world cases covering major machine learning algorithms and be comfortable in performing machine learning with MATLAB.

MATLAB for Machine Learning. Unlock the power of deep learning for swift and enhanced results - Second Edition

Giuseppe Ciaburro

Discover why the MATLAB programming environment is highly favored by researchers and math experts for machine learning with this guide which is designed to enhance your proficiency in both machine learning and deep learning using MATLAB, paving the way for advanced applications.By navigating the versatile machine learning tools in the MATLAB environment, you’ll learn how to seamlessly interact with the workspace. You’ll then move on to data cleansing, data mining, and analyzing various types of data in machine learning, and visualize data values on a graph. As you progress, you’ll explore various classification and regression techniques, skillfully applying them with MATLAB functions.This book teaches you the essentials of neural networks, guiding you through data fitting, pattern recognition, and cluster analysis. You’ll also explore feature selection and extraction techniques for performance improvement through dimensionality reduction. Finally, you’ll leverage MATLAB tools for deep learning and managing convolutional neural networks.By the end of the book, you’ll be able to put it all together by applying major machine learning algorithms in real-world scenarios.

Microsoft Azure Machine Learning. Explore predictive analytics using step-by-step tutorials and build models to make prediction in a jiffy with a few mouse clicks

Sumit Mund

The book is intended for those who want to learn how to use Azure Machine Learning. Perhaps you already know a bit about Machine Learning, but have never used ML Studio in Azure; or perhaps you are an absolute newbie. In either case, this book will get you up-and-running quickly.

Microsoft Power BI Quick Start Guide. Bring your data to life through data modeling, visualization, digital storytelling, and more - Second Edition

Devin Knight, Erin Ostrowsky, Mitchell Pearson, Bradley...

This revised edition has been fully updated to reflect the latest enhancements to Power BI. It includes a new chapter dedicated to dataflow, and covers all the essential concepts such as installation, designing effective data models, as well as building basic dashboards and visualizations to help you and your organization make better business decisions.You’ll learn how to obtain data from a variety of sources and clean it using Power BI Query Editor. You’ll then find out how you can design your data model to navigate and explore relationships within it and build DAX formulas to make your data easier to work with. Visualizing your data is a key element in this book, and you’ll get to grips rapidly with data visualization styles and enhanced digital storytelling techniques. In addition, you will acquire the skills to build your own dataflows, understand the Common Data Model, and automate data flow refreshes to eradicate data cleansing inefficiency.This guide will help you understand how to administer your organization's Power BI environment so that deployment can be made seamless, data refreshes can run properly, and security can be fully implemented.By the end of this Power BI book, you’ll have a better understanding of how to get the most out of Power BI to perform effective business intelligence.

MLOps with Red Hat OpenShift. A cloud-native approach to machine learning operations

Ross Brigoli, Faisal Masood

MLOps with OpenShift offers practical insights for implementing MLOps workflows on the dynamic OpenShift platform. As organizations worldwide seek to harness the power of machine learning operations, this book lays the foundation for your MLOps success. Starting with an exploration of key MLOps concepts, including data preparation, model training, and deployment, you’ll prepare to unleash OpenShift capabilities, kicking off with a primer on containers, pods, operators, and more.With the groundwork in place, you’ll be guided to MLOps workflows, uncovering the applications of popular machine learning frameworks for training and testing models on the platform.As you advance through the chapters, you’ll focus on the open-source data science and machine learning platform, Red Hat OpenShift Data Science, and its partner components, such as Pachyderm and Intel OpenVino, to understand their role in building and managing data pipelines, as well as deploying and monitoring machine learning models.Armed with this comprehensive knowledge, you’ll be able to implement MLOps workflows on the OpenShift platform proficiently.

Mobile Deep Learning with TensorFlow Lite, ML Kit and Flutter. Build scalable real-world projects to implement end-to-end neural networks on Android and iOS

Anubhav Singh, Rimjhim Bhadani

Deep learning is rapidly becoming the most popular topic in the mobile app industry. This book introduces trending deep learning concepts and their use cases with an industrial and application-focused approach. You will cover a range of projects covering tasks such as mobile vision, facial recognition, smart artificial intelligence assistant, augmented reality, and more.With the help of eight projects, you will learn how to integrate deep learning processes into mobile platforms, iOS, and Android. This will help you to transform deep learning features into robust mobile apps efficiently. You’ll get hands-on experience of selecting the right deep learning architectures and optimizing mobile deep learning models while following an application oriented-approach to deep learning on native mobile apps. We will later cover various pre-trained and custom-built deep learning model-based APIs such as machine learning (ML) Kit through Firebase. Further on, the book will take you through examples of creating custom deep learning models with TensorFlow Lite. Each project will demonstrate how to integrate deep learning libraries into your mobile apps, right from preparing the model through to deployment.By the end of this book, you’ll have mastered the skills to build and deploy deep learning mobile applications on both iOS and Android.

Model Context Protocol. Master the integration of AI Agents and Model Context Protocol with real-world applications

Mehul Gupta, Niladri Sen

This book offers a detailed introduction to the groundbreaking field of AI agents and Model Context Protocol (MCP). The first section delves into generative AI and large language models (LLMs), exploring how these technologies power modern AI systems. From there, the book introduces the concept of AI agents—autonomous systems capable of executing tasks with varying levels of complexity. Moving into practical applications, the book focuses on Model Context Protocol, explaining its key components and how it enables effective interaction between AI and various software tools. Each chapter offers step-by-step instructions for setting up MCP servers for popular tools like Gmail, YouTube, GitHub, and more, empowering readers to automate tasks and streamline workflows. The book concludes by addressing the future of MCP, its potential risks, and how to stay safe while using these advanced technologies. Whether you're a beginner or experienced practitioner, this guide will deepen your understanding of AI and enhance your ability to leverage cutting-edge automation in daily operations.

Moodle Gradebook - Second Edition. - Second Edition

Rebecca Barrington

This book is for teachers and administrators who have experience with Moodle. Basic knowledge of Moodle 2.x will be required, but no prior knowledge of grade functions is needed. This book will help you utilize the full functionality of Version 2.7.