In Today's Data-Driven World, The Ability To Harness The Power Of Predictive Analytics And Machine Learning Has Become A Pivotal Force In Shaping Innovation Across Industries. This Book, Mastering Azure For Predictive Analytics And Machine Learning, Aims To Bridge The Gap Between Cloud Technology And The Analytical Tools Needed To Drive Insights From Complex Data. Our Objective Is To Provide Readers With The Foundational Knowledge And Advanced Techniques Necessary To Leverage Microsoft Azure For Predictive Modeling And Machine Learning Applications. The Structure Of This Book Offers A Comprehensive Exploration Of The Tools, Methodologies, And Best Practices That Define Modern Analytics And Machine Learning In The Cloud. From Setting Up Your Azure Environment To Deploying Machine Learning Models, We Cover Each Stage With Practical Examples And Detailed Guidance. The Content Is Designed For A Broad Audience, Including Students, Data Scientists, It Professionals, And Business Leaders Who Seek To Use Azure’s Capabilities To Make Data-Informed Decisions. Drawing From The Latest Industry Research And Real-World Use Cases, This Book Not Only Provides Theoretical Knowledge But Also Equips Readers With Hands-On Skills They Can Apply In Real-Time Data Projects. Each Chapter Balances Depth With Accessibility, Covering Topics Like Data Preparation, Model Building, And Cloud-Based Deployment, While Also Touching On Critical Issues Such As Scalability, Security, And Automation. Additionally, We Highlight Best Practices For Managing Azure’s Infrastructure And Optimizing Machine Learning Workflows Within The Platform. The Inspiration For This Book Comes From The Recognition Of The Growing Role That Cloud Platforms Like Azure Play In Transforming How Organizations Use Data To Innovate And Compete. We Are Immensely Thankful To Chancellor Shri Shiv Kumar Gupta Of Maharaja Agrasen Himalayan Garhwal University For His Support And Commitment To Academic And Technological Excellence, Which Has Been Instrumental In Making This Book A Reality. We Hope That Mastering Azure For Predictive Analytics And Machine Learning Will Be A Valuable Resource For Anyone Looking To Deepen Their Understanding Of How Cloud Computing And Machine Learning Can Converge To Unlock The Full Potential Of Predictive Analytics. The Knowledge Contained In These Pages Is Intended To Empower Readers To Lead Transformative Data Projects With Confidence. Thank You For Embarking On This Journey With Us. Authors

This book will help you learn how to build a scalable end-to-end machine learning pipeline in Azure from experimentation and training to optimization and deployment. By the end of this book, you will learn to build complex distributed systems and scalable cloud infrastructure using powerful machine learning algorithms to compute insights.

This book provides you with the skills necessary to get started with Azure Machine Learning to build predictive models as quickly as possible, in a very intuitive way, whether you are completely new to predictive analysis or an existing practitioner. The book starts by exploring ML Studio, the browser-based development environment, and explores the first step—data exploration and visualization. You will then build different predictive models using both supervised and unsupervised algorithms, including a simple recommender system. The focus then shifts to learning how to deploy a model to production and publishing it as an API. The book ends with a couple of case studies using all the concepts and skills you have learned throughout the book to solve real-world problems.

Microsoft Azure Essentials from Microsoft Press is a series of free ebooks designed to help you advance your technical skills with Microsoft Azure. This third ebook in the series introduces Microsoft Azure Machine Learning, a service that a developer can use to build predictive analytics models (using training datasets from a variety of data sources) and then easily deploy those models for consumption as cloud web services. The ebook presents an overview of modern data science theory and principles, the associated workflow, and then covers some of the more common machine learning algorithms in use today. It builds a variety of predictive analytics models using real world data, evaluates several different machine learning algorithms and modeling strategies, and then deploys the finished models as machine learning web services on Azure within a matter of minutes. The ebook also expands on a working Azure Machine Learning predictive model example to explore the types of client and server applications you can create to consume Azure Machine Learning web services. Watch Microsoft Press’s blog and Twitter (@MicrosoftPress) to learn about other free ebooks in the Microsoft Azure Essentials series.

Implement machine learning, cognitive services, and artificial intelligence solutions by leveraging Azure cloud technologies Key FeaturesLearn advanced concepts in Azure ML and the Cortana Intelligence Suite architectureExplore ML Server using SQL Server and HDInsight capabilitiesImplement various tools in Azure to build and deploy machine learning modelsBook Description Implementing Machine learning (ML) and Artificial Intelligence (AI) in the cloud had not been possible earlier due to the lack of processing power and storage. However, Azure has created ML and AI services that are easy to implement in the cloud. Hands-On Machine Learning with Azure teaches you how to perform advanced ML projects in the cloud in a cost-effective way. The book begins by covering the benefits of ML and AI in the cloud. You will then explore Microsoft’s Team Data Science Process to establish a repeatable process for successful AI development and implementation. You will also gain an understanding of AI technologies available in Azure and the Cognitive Services APIs to integrate them into bot applications. This book lets you explore prebuilt templates with Azure Machine Learning Studio and build a model using canned algorithms that can be deployed as web services. The book then takes you through a preconfigured series of virtual machines in Azure targeted at AI development scenarios. You will get to grips with the ML Server and its capabilities in SQL and HDInsight. In the concluding chapters, you’ll integrate patterns with other non-AI services in Azure. By the end of this book, you will be fully equipped to implement smart cognitive actions in your models. What you will learnDiscover the benefits of leveraging the cloud for ML and AIUse Cognitive Services APIs to build intelligent botsBuild a model using canned algorithms from Microsoft and deploy it as a web serviceDeploy virtual machines in AI development scenariosApply R, Python, SQL Server, and Spark in AzureBuild and deploy deep learning solutions with CNTK, MMLSpark, and TensorFlowImplement model retraining in IoT, Streaming, and Blockchain solutionsExplore best practices for integrating ML and AI functions with ADLA and logic appsWho this book is for If you are a data scientist or developer familiar with Azure ML and cognitive services and want to create smart models and make sense of data in the cloud, this book is for you. You’ll also find this book useful if you want to bring powerful machine learning services into your cloud applications. Some experience with data manipulation and processing, using languages like SQL, Python, and R, will aid in understanding the concepts covered in this book

Get up-to-speed with Microsoft's AI Platform. Learn to innovate and accelerate with open and powerful tools and services that bring artificial intelligence to every data scientist and developer. Artificial Intelligence (AI) is the new normal. Innovations in deep learning algorithms and hardware are happening at a rapid pace. It is no longer a question of should I build AI into my business, but more about where do I begin and how do I get started with AI? Written by expert data scientists at Microsoft, Deep Learning with the Microsoft AI Platform helps you with the how-to of doing deep learning on Azure and leveraging deep learning to create innovative and intelligent solutions. Benefit from guidance on where to begin your AI adventure, and learn how the cloud provides you with all the tools, infrastructure, and services you need to do AI. What You'll Learn Become familiar with the tools, infrastructure, and services available for deep learning on Microsoft Azure such as Azure Machine Learning services and Batch AI Use pre-built AI capabilities (Computer Vision, OCR, gender, emotion, landmark detection, and more) Understand the common deep learning models, including convolutional neural networks (CNNs), recurrent neural networks (RNNs), generative adversarial networks (GANs) with sample code and understand how the field is evolving Discover the options for training and operationalizing deep learning models on Azure Who This Book Is For Professional data scientists who are interested in learning more about deep learning and how to use the Microsoft AI platform. Some experience with Python is helpful.

Cybellium Ltd is dedicated to empowering individuals and organizations with the knowledge and skills they need to navigate the ever-evolving computer science landscape securely and learn only the latest information available on any subject in the category of computer science including: - Information Technology (IT) - Cyber Security - Information Security - Big Data - Artificial Intelligence (AI) - Engineering - Robotics - Standards and compliance Our mission is to be at the forefront of computer science education, offering a wide and comprehensive range of resources, including books, courses, classes and training programs, tailored to meet the diverse needs of any subject in computer science. Visit https://www.cybellium.com for more books.