AI/Machine Learning Inference Explained: A Beginner's Guide
AI/Machine Learning Inference Explained: A Beginner's Guide

Author: M.B. Chatfield

Publisher:

Published:

Total Pages: 91

ISBN-13:

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Unleash the Power of AI with Machine Learning Inference In today's data-driven world, artificial intelligence (AI) is rapidly transforming industries and reshaping our lives. At the heart of this revolution lies machine learning, which empowers computers to learn from vast amounts of data and make intelligent decisions without explicit programming. AI/Machine Learning Inference Explained: A Beginner's Guide is your comprehensive guide to understanding and implementing inference, the crucial process of applying machine learning models to real-world problems. Through clear explanations you'll gain a solid foundation in the principles and practices of inference, enabling you to: Grasp the fundamental concepts of machine learning and AI Discover the different types of machine learning models Understand the role of inference in machine learning Learn various inference techniques, including classification, regression, and anomaly detection Apply inference to solve real-world problems in various domains Whether you're a tech enthusiast, a data analyst, or a budding AI professional, this book will equip you with the knowledge and skills you need to harness the power of machine learning inference and make a meaningful impact in the AI landscape. Embrace the future of AI: Start learning machine learning inference today! #AIinference #MachineLearning #AI #FutureofTechnology #DataScience #ArtificialIntelligence #MachineLearningBook #AIbook #AIforBeginners #PredictiveAnalytics #AIInnovation #BigData #DeepLearning #TechTrends #DataDriven #LearnAI #AIApplications

AI Inference Explained: A Beginner's Guide to Understanding
AI Inference Explained: A Beginner's Guide to Understanding

Author: M.B. Chatfield

Publisher:

Published:

Total Pages: 104

ISBN-13:

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Demystify AI Inference and Unleash the Power of Machine Learning In the era of big data and artificial intelligence (AI), the ability to extract meaningful insights from vast amounts of information is crucial. AI inference, the process of applying machine learning models to real-world data, is at the heart of this transformative technology. AI Inference Explained: A Beginner's Guide to Understanding is your comprehensive guide to unlocking the power of AI inference. Through clear explanations, engaging examples, and hands-on exercises, you'll gain a solid foundation in the principles and practices of inference, enabling you to: Grasp the fundamental concepts of AI and machine learning Discover the different types of machine learning models Understand the role of inference in machine learning Learn various inference techniques, including classification, regression, and anomaly detection Apply inference to solve real-world problems in various domains Develop and implement machine learning inference models using popular Python libraries Whether you're a tech enthusiast, a data analyst, or a budding AI professional, this book will equip you with the knowledge and skills you need to navigate the world of AI inference and make a meaningful impact. Embrace the future of AI: Start learning machine learning inference today!

Advances in Financial Machine Learning
Advances in Financial Machine Learning

Author: Marcos Lopez de Prado

Publisher: John Wiley & Sons

Published: 2018-01-23

Total Pages: 395

ISBN-13: 1119482119

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Learn to understand and implement the latest machine learning innovations to improve your investment performance Machine learning (ML) is changing virtually every aspect of our lives. Today, ML algorithms accomplish tasks that – until recently – only expert humans could perform. And finance is ripe for disruptive innovations that will transform how the following generations understand money and invest. In the book, readers will learn how to: Structure big data in a way that is amenable to ML algorithms Conduct research with ML algorithms on big data Use supercomputing methods and back test their discoveries while avoiding false positives Advances in Financial Machine Learning addresses real life problems faced by practitioners every day, and explains scientifically sound solutions using math, supported by code and examples. Readers become active users who can test the proposed solutions in their individual setting. Written by a recognized expert and portfolio manager, this book will equip investment professionals with the groundbreaking tools needed to succeed in modern finance.

Data Centric Artificial Intelligence: A Beginner’s Guide
Data Centric Artificial Intelligence: A Beginner’s Guide

Author: Parikshit N. Mahalle

Publisher: Springer Nature

Published: 2023-11-11

Total Pages: 137

ISBN-13: 9819963532

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This book discusses the best research roadmaps, strategies, and challenges in data-centric approach of artificial intelligence (AI) in various domains. It presents comparative studies of model-centric and data-centric AI. It also highlights different phases in data-centric approach and data-centric principles. The book presents prominent use cases of data-centric AI. It serves as a reference guide for researchers and practitioners in academia and industry.

Microsoft Azure AI: A Beginner’s Guide
Microsoft Azure AI: A Beginner’s Guide

Author: Rekha Kodali

Publisher: BPB Publications

Published: 2022-04-21

Total Pages: 271

ISBN-13: 9355510519

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Explore Azure AI Platform KEY FEATURES ● Easy-to-follow tutorial for getting started with the Azure AI platform. ● Integrated platform for developing, deploying, and managing AI apps. ● Includes real-world scenarios and use-cases to fully explore Azure AI Platform. DESCRIPTION Microsoft Azure AI A Beginner's Guide explains the fundamentals of Azure AI and some more advanced topics. The sole objective of the book is to provide hands-on experience working with the various services, APIs, and tools available in the Azure AI Platform. This book begins by discussing the fundamentals of the Azure AI platform and the essential principles behind the Azure AI ecosystem and services. Readers will become familiar with the essential services, use cases, and examples provided by Azure AI Platform and Services, including Azure Cognitive Services, Azure Computer Vision, Azure Applied AI Services, and Azure Machine Learning. The author focuses on teaching how to utilize Azure Cognitive services to construct intelligent apps, including Image Processing, Object Detection, Text Recognition, OCR, Spatial Analysis, and Face Recognition using Computer Vision. Readers can investigate Azure Applied AI Services, including Form Recognizer, Metrics Advisor, Cognitive Search, Immersive Reader, Video Analyzer, and Azure Bot Service. Bot Framework and the Bot Framework Emulator will be explored in further detail, and how they can be used in AI applications to improve their conversational user interfaces. With Azure Machine Learning Studio, you will also learn to incorporate machine learning into your enterprise-level applications. WHAT YOU WILL LEARN ● Get familiar with Azure AI Platform and the cognitive capabilities of Azure. ● Learn to create apps that can process photos, detect faces, and detect objects. ● Utilize OCR, handwriting recognition, and spatial analysis in your development. ● Learn about Azure AI services like Form Recognizer, Metrics Advisor, Cognitive Search, Azure Immersive Reader, and Video Analyzer. ● Try out several NLP applications with the Azure BOT framework. WHO THIS BOOK IS FOR This book teaches AI developers, machine learning engineers, .NET developers, and architects how to swiftly develop intelligent applications utilizing the Azure AI Platform. Knowledge of.NET or.NET Core is strongly advised to get the most out of the book. TABLE OF CONTENTS 1 .Azure AI Platform and Services 2. Azure Computer Vision - Image Analysis, Processing, Content Moderation, Object and Face Detection 3. Computer Vision - Text Recognition, Optical Character Recognition, Spatial Analysis 4. Azure Cognitive Services - Custom Applications leveraging Decision, Language, Speech, Web Search 5. Azure Applied AI Services 6. Azure Applied AI Services -BOTs– A Brief Introduction 7. Machine Learning-Infusing ML in Custom Applications using ML.NET 8. Machine Learning - Using Azure ML Studio

Encyclopedia of Artificial Intelligence
Encyclopedia of Artificial Intelligence

Author: Juan Ramon Rabunal

Publisher: IGI Global

Published: 2009-01-01

Total Pages: 1640

ISBN-13: 1599048507

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"This book is a comprehensive and in-depth reference to the most recent developments in the field covering theoretical developments, techniques, technologies, among others"--Provided by publisher.

Deep Learning Networks
Deep Learning Networks

Author: Jayakumar Singaram

Publisher: Springer Nature

Published: 2023-12-03

Total Pages: 173

ISBN-13: 3031392442

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This textbook presents multiple facets of design, development and deployment of deep learning networks for both students and industry practitioners. It introduces a deep learning tool set with deep learning concepts interwoven to enhance understanding. It also presents the design and technical aspects of programming along with a practical way to understand the relationships between programming and technology for a variety of applications. It offers a tutorial for the reader to learn wide-ranging conceptual modeling and programming tools that animate deep learning applications. The book is especially directed to students taking senior level undergraduate courses and to industry practitioners interested in learning about and applying deep learning methods to practical real-world problems.

It's All Analytics!
It's All Analytics!

Author: Scott Burk

Publisher: CRC Press

Published: 2020-05-25

Total Pages: 194

ISBN-13: 100006722X

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It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, "analytics," is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.

Python Programming, Deep Learning
Python Programming, Deep Learning

Author: Anthony Adams

Publisher: Anthony Adams

Published: 2021-12-17

Total Pages: 315

ISBN-13:

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Easily Boost Your Skills In Python Programming & Become A Master In Deep Learning & Data Analysis! 💻 Python is an interpreted, high-level, general-purpose programming language that emphasizes code readability with its notable use of significant whitespace. What makes Python so popular in the IT industry is that it uses an object-oriented approach, which enables programmers to write clear, logical code for all types of projects, whether big or small. Hone your Python Programming skills and gain a sharp edge over other programmers the EASIEST way possible... with this practical beginner’s guide! In his 3-in-1 Python crash course for beginners, Anthony Adams gives novices like you simple, yet efficient tips and tricks to become a MASTER in Python coding for artificial intelligence, neural networks, machine learning, and data science/analysis! Here’s what you’ll get: ✅ Highly innovative ways to boost your understanding of Python programming, data analysis, and machine learning ✅ Quickly and effectively stop fraud with machine learning ✅ Practical and efficient exercises that make understanding Python quick & easy And so much more! As a beginner, you might feel a bit intimidated by the complexities of coding. Add the fact that most Python Programming crash course guides make learning harder than it has to be! ✓ With the help of this 3-in-1 guide, you will be given carefully sequenced Python Programming lessons that’ll maximize your understanding, and equip you with all the skills for real-life application! ★ Thrive in the IT industry with this comprehensive Python Programming crash course! ★ Scroll up, Click on “Buy Now”, and Start Learning Today!

Python Machine Learning
Python Machine Learning

Author: Ryan Turner

Publisher: Publishing Factory

Published: 2020-04-18

Total Pages: 185

ISBN-13:

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Are you a novice programmer who wants to learn Python Machine Learning? Are you worried about how to translate what you already know into Python? This book will help you overcome those problems! As machines get ever more complex and perform more and more tasks to free up our time, so it is that new ideas are developed to help us continually improve their speed and abilities. One of these is Python and in Python Machine Learning: 3 books in 1 - The Ultimate Beginner's Guide to Learn Python Machine Learning Step by Step using Scikit-Learn and Tensorflow, you will discover information and advice on: Book 1 • What machine learning is • The history of machine learning • Approaches to machine learning • Support vector machines • Machine learning and neural networks • The Internet of Things (IoT) • The future of machine learning • And more… Book 2 • The principles surrounding Python • Different types of networks so you can choose what works best for you • Features of the system • Real world feature engineering • Understanding the techniques of semi-supervised learning • And more… Book 3 • How advanced tensorflow can be used • Neural network models and how to get the most from them • Machine learning with Generative Adversarial Networks • Translating images with cross domain GANs • TF clusters and how to use them • How to debug TF models • And more… This book has been written specifically for beginners and the simple, step by step instructions and plain language make it an ideal place to start for anyone who has a passing interest in this fascinating subject. Python really is an amazing system and can provide you with endless possibilities when you start learning about it. Get a copy of Python Machine Learning today and see where the future lies.