Download or read book Microsoft Copilot for Data Science written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on with total page 66 pages. Available in PDF, EPUB and Kindle. Book excerpt: Drowning in data but struggling to extract meaningful insights? Enter Copilot, your AI-powered data science partner. This revolutionary tool streamlines your workflow, automates tedious tasks, and empowers you to uncover hidden patterns and make data-driven decisions faster than ever before. Copilot doesn't just write code - it becomes an extension of your analytical mind. It automates repetitive tasks like data cleaning, feature engineering, and report generation, freeing you to focus on the strategic aspects of analysis and problem-solving. Imagine: Building and training machine learning models with just a few lines of code, while Copilot optimizes hyperparameters for peak performance. Generating clear and compelling data visualizations that bring your insights to life, without the need for manual coding. Asking natural language questions about your data and receiving insightful answers, along with suggested visualizations for deeper exploration. Copilot isn't just a tool; it's a paradigm shift in data science. It democratizes the field, making advanced analytics accessible to those with limited coding experience. Whether you're a seasoned data scientist or just starting your journey, Copilot empowers you to: Boost Efficiency: Automate repetitive tasks and free up valuable time for strategic analysis. Gain Deeper Insights: Uncover hidden patterns and relationships within your data that might be missed with manual analysis. Make Better Decisions: Leverage data-driven insights to make informed choices that drive positive outcomes. Embrace the future of data science with Copilot. This comprehensive guide delves into the power of this AI assistant, equipping you with the knowledge and skills to: Set up and configure Copilot within your preferred data science environment. Master data wrangling, cleaning, and feature engineering with Copilot's assistance. Generate impactful data visualizations that effectively communicate your findings. Build, train, and deploy machine learning models with unprecedented efficiency. Automate repetitive tasks and streamline your entire data science workflow. Unlock the full potential of your data and transform your analytical capabilities with Copilot. This book is your roadmap to a more efficient, insightful, and impactful data science journey.

Download or read book Foundations of Data Science written by Avrim Blum and published by Cambridge University Press. This book was released on 2020-01-23 with total page 433 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides an introduction to the mathematical and algorithmic foundations of data science, including machine learning, high-dimensional geometry, and analysis of large networks. Topics include the counterintuitive nature of data in high dimensions, important linear algebraic techniques such as singular value decomposition, the theory of random walks and Markov chains, the fundamentals of and important algorithms for machine learning, algorithms and analysis for clustering, probabilistic models for large networks, representation learning including topic modelling and non-negative matrix factorization, wavelets and compressed sensing. Important probabilistic techniques are developed including the law of large numbers, tail inequalities, analysis of random projections, generalization guarantees in machine learning, and moment methods for analysis of phase transitions in large random graphs. Additionally, important structural and complexity measures are discussed such as matrix norms and VC-dimension. This book is suitable for both undergraduate and graduate courses in the design and analysis of algorithms for data.

Download or read book Learn Microsoft Fabric written by Arshad Ali and published by Packt Publishing Ltd. This book was released on 2024-02-29 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Harness the power of Microsoft Fabric to develop data analytics solutions for various use cases guided by step-by-step instructions Key Features Explore Microsoft Fabric and its features through real-world examples Build data analytics solutions for lakehouses, data warehouses, real-time analytics, and data science Monitor, manage, and administer your Fabric platform and analytics system to ensure flexibility, performance, security, and control Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDiscover the capabilities of Microsoft Fabric, the premier unified solution designed for the AI era, seamlessly combining data integration, OneLake, transformation, visualization, universal security, and a unified business model. This book provides an overview of Microsoft Fabric, its components, and the wider analytics landscape. In this book, you'll explore workloads such as Data Factory, Synapse Data Engineering, data science, data warehouse, real-time analytics, and Power BI. You’ll learn how to build end-to-end lakehouse and data warehouse solutions using the medallion architecture, unlock the real-time analytics, and implement machine learning and AI models. As you progress, you’ll build expertise in monitoring workloads and administering Fabric across tenants, capacities, and workspaces. The book also guides you step by step through enhancing security and governance practices in Microsoft Fabric and implementing CI/CD workflows with Azure DevOps or GitHub. Finally, you’ll discover the power of Copilot, an AI-driven assistant that accelerates your analytics journey. By the end of this book, you’ll have unlocked the full potential of AI-driven data analytics, gaining a comprehensive understanding of the analytics landscape and mastery over the essential concepts and principles of Microsoft Fabric.What you will learn Get acquainted with the different services available in Microsoft Fabric Build end-to-end data analytics solution to scale and manage high performance Integrate data from different types of data sources Apply transformation with Spark, Notebook, and T-SQL Understand and implement real-time stream processing and data science capabilities Perform end-to-end processes for building data analytics solutions in the AI era Drive insights by leveraging Power BI for reporting and visualization Improve productivity with AI assistance and Copilot integration Who this book is for This book is for data professionals, including data analysts, data engineers, data scientists, data warehouse developers, ETL developers, business analysts, AI/ML professionals, software developers, and Chief Data Officers who want to build a future-ready data analytics solution for long-term success in the AI era. For PySpark and SQL students entering the data analytics field, this book offers a broad foundation for developing the skills to build end-to-end analytics systems for various use cases. Basic knowledge of SQL and Spark is assumed.

Download or read book Microsoft Copilot Pro written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on 2024-05-29 with total page 152 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Discover the ultimate resource for mastering Microsoft Copilot Pro with our comprehensive guide. Unlock the full potential of this powerful tool to streamline operations, enhance collaboration, and boost productivity across your organization. From optimizing workflows to ensuring data security and compliance, our detailed insights and practical tips will guide you every step of the way. Whether you're a novice looking to get started or an experienced user seeking advanced strategies, this guide has everything you need to harness the full power of Copilot Pro and take your productivity to new heights

Download or read book Mastering Microsoft Fabric written by Debananda Ghosh and published by Springer Nature. This book was released on with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Pattern Recognition and Machine Learning written by Christopher M. Bishop and published by Springer. This book was released on 2016-08-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first textbook on pattern recognition to present the Bayesian viewpoint. The book presents approximate inference algorithms that permit fast approximate answers in situations where exact answers are not feasible. It uses graphical models to describe probability distributions when no other books apply graphical models to machine learning. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

Download or read book The Fourth Paradigm written by Anthony J. G. Hey and published by . This book was released on 2009 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Foreword. A transformed scientific method. Earth and environment. Health and wellbeing. Scientific infrastructure. Scholarly communication.

Download or read book Data Science Neural Networks Deep Learning LLMs and Power BI written by Jagdish Krishanlal Arora and published by Jagdish Krishanlal Arora. This book was released on 2024-08-29 with total page 173 pages. Available in PDF, EPUB and Kindle. Book excerpt: I wrote this book as I got an interview offer for Data Analyst. There they asked me a lot of questions and there was an exam. This helped me a lot to write the book based on the interview questions faced by me and the knowledge gained by working on AI projects. I then added all my other knowledge working as a Data Analyst on my other projects and wrote the book. Technical books need a lot of attention, as they need deep checks, but I tried to do my best. Not everything can be included in detail, it is impossible. I have tried to include everything related to Data Science that is presently going on in the industry and the world.

Download or read book Boosting Productivity with Microsoft Copilot written by StoryBuddiesPlay and published by StoryBuddiesPlay. This book was released on 2024-06-05 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: In today's fast-paced work environment, maximizing productivity is essential. Enter Copilot, a revolutionary AI assistant poised to transform the way we work. This comprehensive guide delves into Copilot's capabilities, exploring its impact across various industries and outlining best practices for responsible utilization. Unleash Unparalleled Efficiency: Streamlined workflows: Discover how Copilot automates repetitive tasks, manages project timelines, and boosts collaboration within teams, freeing you to focus on strategic initiatives. Personalized to your needs: Learn how Copilot adapts to your unique work style, offering custom prompts, generating tailored reports, and integrating seamlessly with your preferred tools. Enhanced for every role: Explore industry-specific templates and functionalities, empowering scientists, writers, marketers, and more to achieve remarkable results. The Future of Work is Collaborative: Beyond automation: Forget about mindless automation. Copilot fosters a collaborative environment, augmenting your capabilities and acting as an intelligent partner. Human-machine synergy: Imagine brainstorming sessions facilitated by AI, or receiving real-time instructions overlaid on your workspace. Copilot unlocks a future of seamless human-machine collaboration. Evolving alongside you: Witness Copilot's continuous learning process. As you interact, it personalizes suggestions, anticipates needs, and becomes an extension of your thought process. Master Copilot for Peak Productivity: Responsible AI practices: Gain valuable insights on using Copilot ethically, ensuring your work maintains originality and upholds the highest ethical standards. Advanced techniques for power users: Dive deep into advanced functionalities like custom AI model training and natural language processing for complex tasks. Unlock your full potential: Learn how to leverage Copilot's strengths to overcome writer's block, generate creative content, and analyze complex data sets, propelling you towards peak productivity. Embrace the Future of Work: Copilot represents a paradigm shift in the way we approach work. This guide equips you with the knowledge and strategies to harness its power responsibly. Whether you're a seasoned professional or just starting out, Copilot is your key to unlocking a future of enhanced productivity and human-machine collaboration. Don't wait to get started! Explore Copilot's potential and revolutionize the way you work.

Download or read book Azure OpenAI Service for Cloud Native Applications written by Adrián González Sánchez and published by "O'Reilly Media, Inc.". This book was released on 2024-06-27 with total page 275 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get the details, examples, and best practices you need to build generative AI applications, services, and solutions using the power of Azure OpenAI Service. With this comprehensive guide, Microsoft AI specialist Adrián González Sánchez examines the integration and utilization of Azure OpenAI Service—using powerful generative AI models such as GPT-4 and GPT-4o—within the Microsoft Azure cloud computing platform. To guide you through the technical details of using Azure OpenAI Service, this book shows you how to set up the necessary Azure resources, prepare end-to-end architectures, work with APIs, manage costs and usage, handle data privacy and security, and optimize performance. You'll learn various use cases where Azure OpenAI Service models can be applied, and get valuable insights from some of the most relevant AI and cloud experts. Ideal for software and cloud developers, product managers, architects, and engineers, as well as cloud-enabled data scientists, this book will help you: Learn how to implement cloud native applications with Azure OpenAI Service Deploy, customize, and integrate Azure OpenAI Service with your applications Customize large language models and orchestrate knowledge with company-owned data Use advanced roadmaps to plan your generative AI project Estimate cost and plan generative AI implementations for adopter companies

Download or read book Hands On Machine Learning with Microsoft Excel 2019 written by Julio Cesar Rodriguez Martino and published by Packt Publishing Ltd. This book was released on 2019-04-30 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: A practical guide to getting the most out of Excel, using it for data preparation, applying machine learning models (including cloud services) and understanding the outcome of the data analysis. Key FeaturesUse Microsoft's product Excel to build advanced forecasting models using varied examples Cover range of machine learning tasks such as data mining, data analytics, smart visualization, and more Derive data-driven techniques using Excel plugins and APIs without much code required Book Description We have made huge progress in teaching computers to perform difficult tasks, especially those that are repetitive and time-consuming for humans. Excel users, of all levels, can feel left behind by this innovation wave. The truth is that a large amount of the work needed to develop and use a machine learning model can be done in Excel. The book starts by giving a general introduction to machine learning, making every concept clear and understandable. Then, it shows every step of a machine learning project, from data collection, reading from different data sources, developing models, and visualizing the results using Excel features and offerings. In every chapter, there are several examples and hands-on exercises that will show the reader how to combine Excel functions, add-ins, and connections to databases and to cloud services to reach the desired goal: building a full data analysis flow. Different machine learning models are shown, tailored to the type of data to be analyzed. At the end of the book, the reader is presented with some advanced use cases using Automated Machine Learning, and artificial neural network, which simplifies the analysis task and represents the future of machine learning. What you will learnUse Excel to preview and cleanse datasetsUnderstand correlations between variables and optimize the input to machine learning modelsUse and evaluate different machine learning models from ExcelUnderstand the use of different visualizationsLearn the basic concepts and calculations to understand how artificial neural networks workLearn how to connect Excel to the Microsoft Azure cloudGet beyond proof of concepts and build fully functional data analysis flowsWho this book is for This book is for data analysis, machine learning enthusiasts, project managers, and someone who doesn't want to code much for performing core tasks of machine learning. Each example will help you perform end-to-end smart analytics. Working knowledge of Excel is required.

Download or read book AI and Data Analytics Applications in Organizational Management written by Merlo, Tereza Raquel and published by IGI Global. This book was released on 2024-02-07 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: Within information sciences and organizational management, a pressing challenge emerges; How can we harness the transformative power of artificial intelligence (AI) and data analytics? As industries grapple with a deluge of data and the imperative to make informed decisions swiftly, the gap between data collection and actionable insights widens. Professionals in various sectors are in a race to unlock AI's full potential to drive operational efficiency, enhance decision-making, and gain a competitive edge. However, navigating this intricate terrain, laden with ethical considerations and interdisciplinary complexity, has proven to be a formidable undertaking. AI and Data Analytics Applications in Organizational Management, combines rigorous scholarship with practicality. It traverses the spectrum from theoretical foundations to real-world applications, making it indispensable for those seeking to implement AI-driven data analytics in their organizations. Moreover, it delves into the ethical and societal dimensions of this revolution, ensuring that the journey toward innovation is paved with responsible considerations. For researchers, scholars, and practitioners yearning to unleash the potential of AI in organizational management, this book is the key to not only understanding the landscape but also charting a course toward transformative change.

Download or read book Microsoft Data Analytics For Dummies written by Jared Decker and published by For Dummies. This book was released on 2025-05-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master Microsoft Data Analytics tools with the book series trusted by millions across the world Microsoft leads the software industry in analytics with some of the most comprehensive and powerful data analytics tools currently available. The demand for people who can use and understand these tools remains sky-high and increases every day. In Microsoft Data Analytics For Dummies, the authors have created a straightforward and easy to understand introduction to readers who want to leverage Microsoft products for data analysis. Written by experienced data infrastructure architects, Microsoft Data Analytics For Dummies seeks to flatten and shorten the learning curve typically associated with data analytics. The book includes information about Microsoft data tools, including: · Microsoft Excel, the industry-leading spreadsheet tool · Power Pivot · Power Query · Power BI This book is perfect for non-developers who have a need to use data to support their business decisions without looping in technical personnel. With the newfound ability to rely on data to make better decisions, business executives, managers, and employees will experience previously unreached levels of productivity, effectiveness, and efficiency.

Download or read book Dual Learning written by Tao Qin and published by Springer Nature. This book was released on 2020-11-13 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many AI (and machine learning) tasks present in dual forms, e.g., English-to-Chinese translation vs. Chinese-to-English translation, speech recognition vs. speech synthesis,question answering vs. question generation, and image classification vs. image generation. Dual learning is a new learning framework that leverages the primal-dual structure of AI tasks to obtain effective feedback or regularization signals in order to enhance the learning/inference process. Since it was first introduced four years ago, the concept has attracted considerable attention in multiple fields, and been proven effective in numerous applications, such as machine translation, image-to-image translation, speech synthesis and recognition, (visual) question answering and generation, image captioning and generation, and code summarization and generation. Offering a systematic and comprehensive overview of dual learning, this book enables interested researchers (both established and newcomers) and practitioners to gain a better understanding of the state of the art in the field. It also provides suggestions for further reading and tools to help readers advance the area. The book is divided into five parts. The first part gives a brief introduction to machine learning and deep learning. The second part introduces the algorithms based on the dual reconstruction principle using machine translation, image translation, speech processing and other NLP/CV tasks as the demo applications. It covers algorithms, such as dual semi-supervised learning, dual unsupervised learning and multi-agent dual learning. In the context of image translation, it introduces algorithms including CycleGAN, DualGAN, DiscoGAN cdGAN and more recent techniques/applications. The third part presents various work based on the probability principle, including dual supervised learning and dual inference based on the joint-probability principle and dual semi-supervised learning based on the marginal-probability principle. The fourth part reviews various theoretical studies on dual learning and discusses its connections to other learning paradigms. The fifth part provides a summary and suggests future research directions.

Download or read book Azure Data Scientist Associate Certification Guide written by Andreas Botsikas and published by Packt Publishing Ltd. This book was released on 2021-12-03 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Develop the skills you need to run machine learning workloads in Azure and pass the DP-100 exam with ease Key FeaturesCreate end-to-end machine learning training pipelines, with or without codeTrack experiment progress using the cloud-based MLflow-compatible process of Azure ML servicesOperationalize your machine learning models by creating batch and real-time endpointsBook Description The Azure Data Scientist Associate Certification Guide helps you acquire practical knowledge for machine learning experimentation on Azure. It covers everything you need to pass the DP-100 exam and become a certified Azure Data Scientist Associate. Starting with an introduction to data science, you'll learn the terminology that will be used throughout the book and then move on to the Azure Machine Learning (Azure ML) workspace. You'll discover the studio interface and manage various components, such as data stores and compute clusters. Next, the book focuses on no-code and low-code experimentation, and shows you how to use the Automated ML wizard to locate and deploy optimal models for your dataset. You'll also learn how to run end-to-end data science experiments using the designer provided in Azure ML Studio. You'll then explore the Azure ML Software Development Kit (SDK) for Python and advance to creating experiments and publishing models using code. The book also guides you in optimizing your model's hyperparameters using Hyperdrive before demonstrating how to use responsible AI tools to interpret and debug your models. Once you have a trained model, you'll learn to operationalize it for batch or real-time inferences and monitor it in production. By the end of this Azure certification study guide, you'll have gained the knowledge and the practical skills required to pass the DP-100 exam. What you will learnCreate a working environment for data science workloads on AzureRun data experiments using Azure Machine Learning servicesCreate training and inference pipelines using the designer or codeDiscover the best model for your dataset using Automated MLUse hyperparameter tuning to optimize trained modelsDeploy, use, and monitor models in productionInterpret the predictions of a trained modelWho this book is for This book is for developers who want to infuse their applications with AI capabilities and data scientists looking to scale their machine learning experiments in the Azure cloud. Basic knowledge of Python is needed to follow the code samples used in the book. Some experience in training machine learning models in Python using common frameworks like scikit-learn will help you understand the content more easily.

Download or read book Modern Data Analytics in Excel written by George Mount and published by "O'Reilly Media, Inc.". This book was released on 2024-04-26 with total page 238 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you haven't modernized your data cleaning and reporting processes in Microsoft Excel, you're missing out on big productivity gains. And if you're looking to conduct rigorous data analysis, more can be done in Excel than you think. This practical book serves as an introduction to the modern Excel suite of features along with other powerful tools for analytics. George Mount of Stringfest Analytics shows business analysts, data analysts, and business intelligence specialists how to make bigger gains right from your spreadsheets by using Excel's latest features. You'll learn how to build repeatable data cleaning workflows with Power Query, and design relational data models straight from your workbook with Power Pivot. You'll also explore other exciting new features for analytics, such as dynamic array functions, AI-powered insights, and Python integration. Learn how to build reports and analyses that were previously difficult or impossible to do in Excel. This book shows you how to: Build repeatable data cleaning processes for Excel with Power Query Create relational data models and analysis measures with Power Pivot Pull data quickly with dynamic arrays Use AI to uncover patterns and trends from inside Excel Integrate Python functionality with Excel for automated analysis and reporting

Download or read book Introducing Microsoft Power BI written by Alberto Ferrari and published by Microsoft Press. This book was released on 2016-07-07 with total page 453 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Introducing Microsoft Power BI enables you to evaluate when and how to use Power BI. Get inspired to improve business processes in your company by leveraging the available analytical and collaborative features of this environment. Be sure to watch for the publication of Alberto Ferrari and Marco Russo's upcoming retail book, Analyzing Data with Power BI and Power Pivot for Excel (ISBN 9781509302765). Go to the book's page at the Microsoft Press Store here for more details:http://aka.ms/analyzingdata/details. Learn more about Power BI at https://powerbi.microsoft.com/.