Machine Learning with Dynamics 365 and Power Platform

Learn how to apply the principles of machine learning to  time series modeling with this indispensable resource   Machine Learning for Time Series Forecasting with Python  is an incisive and straightforward examination of one of the most crucial elements of decision-making in finance, marketing, education, and healthcare: time series modeling.  Despite the centrality of time series forecasting, few business analysts are familiar with the power or utility of applying machine learning to time series modeling. Author Francesca Lazzeri, a distinguished machine learning scientist and economist, corrects that deficiency by providing readers with comprehensive and approachable explanation and treatment of the application of machine learning to time series forecasting.  Written for readers who have little to no experience in time series forecasting or machine learning, the book comprehensively covers all the topics necessary to:  Understand time series forecasting concepts, such as stationarity, horizon, trend, and seasonality Prepare time series data for modeling Evaluate time series forecasting models’ performance and accuracy Understand when to use neural networks instead of traditional time series models in time series forecasting  Machine Learning for Time Series Forecasting with Python  is full real-world examples, resources and concrete strategies to help readers explore and transform data and develop usable, practical time series forecasts.  Perfect for entry-level data scientists, business analysts, developers, and researchers, this book is an invaluable and indispensable guide to the fundamental and advanced concepts of machine learning applied to time series modeling.

Your  comprehensive entry-level guide to machine learning   While machine learning expertise doesn’t quite mean you can create your own Turing Test-proof android—as in the movie  Ex Machina —it  is  a form of artificial intelligence and one of the most exciting technological means of identifying opportunities and solving problems fast and on a large scale. Anyone who masters the principles of machine learning is mastering a big part of our tech future and opening up incredible new directions in careers that include fraud detection, optimizing search results, serving real-time ads, credit- scoring, building accurate and sophisticated pricing models—and way, way more.  Unlike most machine learning books, the fully updated 2nd Edition of  Machine Learning For Dummies  doesn’t assume you have years of experience using programming languages such as Python (R source is also included in a downloadable form with comments and explanations), but lets you in on the ground floor, covering the entry-level materials that will get you up and running building models you need to perform practical tasks. It takes a look at the underlying—and fascinating—math principles that power machine learning but also shows that you don’t need to be a math whiz to build fun new tools and apply them to your work and study.  Understand the history of AI and machine learning Work with Python 3.8 and TensorFlow 2.x (and R as a download) Build and test your own models Use the latest datasets, rather than the worn out data found in other books Apply machine learning to real problems Whether you want to learn for college or to enhance your business or career performance, this friendly beginner’s guide is your best introduction to machine learning, allowing you to become quickly confident using this amazing and fast-developing technology that’s impacting lives for the better all over the world.

Your no-nonsense guide to making sense of machine learning Machine learning can be a mind-boggling concept for the masses, but those who are in the trenches of computer programming know just how invaluable it is. Without machine learning, fraud detection, web search results, real-time ads on web pages, credit scoring, automation, and email spam filtering wouldn't be possible, and this is only showcasing just a few of its capabilities. Written by two data science experts, Machine Learning For Dummies offers a much-needed entry point for anyone looking to use machine learning to accomplish practical tasks. Covering the entry-level topics needed to get you familiar with the basic concepts of machine learning, this guide quickly helps you make sense of the programming languages and tools you need to turn machine learning-based tasks into a reality. Whether you're maddened by the math behind machine learning, apprehensive about AI, perplexed by preprocessing data—or anything in between—this guide makes it easier to understand and implement machine learning seamlessly. Grasp how day-to-day activities are powered by machine learning Learn to 'speak' certain languages, such as Python and R, to teach machines to perform pattern-oriented tasks and data analysis Learn to code in R using R Studio Find out how to code in Python using Anaconda Dive into this complete beginner's guide so you are armed with all you need to know about machine learning!

Succeed on the AWS Machine Learning exam or in your next job as a machine learning specialist on the AWS Cloud platform with this hands-on guide  As the most popular cloud service in the world today, Amazon Web Services offers a wide range of opportunities for those interested in the development and deployment of artificial intelligence and machine learning business solutions.  The  AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam  delivers hyper-focused, authoritative instruction for anyone considering the pursuit of the prestigious Amazon Web Services Machine Learning certification or a new career as a machine learning specialist working within the AWS architecture.  From exam to interview to your first day on the job, this study guide provides the domain-by-domain specific knowledge you need to build, train, tune, and deploy machine learning models with the AWS Cloud. And with the practice exams and assessments, electronic flashcards, and supplementary online resources that accompany this Study Guide, you’ll be prepared for success in every subject area covered by the exam.  You’ll also find:  An intuitive and organized layout perfect for anyone taking the exam for the first time or seasoned professionals seeking a refresher on machine learning on the AWS Cloud Authoritative instruction on a widely recognized certification that unlocks countless career opportunities in machine learning and data science Access to the Sybex online learning resources and test bank, with chapter review questions, a full-length practice exam, hundreds of electronic flashcards, and a glossary of key terms  AWS Certified Machine Learning Study Guide: Specialty (MLS-CO1) Exam  is an indispensable guide for anyone seeking to prepare themselves for success on the AWS Certified Machine Learning Specialty exam or for a job interview in the field of machine learning, or who wishes to improve their skills in the field as they pursue a career in AWS machine learning.

Accelerate your digital transformation and break down silos with Microsoft Dynamics 365 It’s no secret that running a business involves several complex parts like managing staff, financials, marketing, and operations—just to name a few. That’s where Microsoft Dynamics 365, the most profitable business management tool, comes in. In Microsoft Dynamics 365 For Dummies, you’ll learn the aspects of the program and each of its applications from Customer Service to Financial Management. With expert author Renato Bellu’s clear instructions and helpful tips, you’ll be managing to your fullest advantage before you know it. Let’s get started! Digitally transform your business by connecting CRM and ERP Use data to make decisions across all business functions Integrate Dynamics 365 with Office 365 and LinkedIn Manage financials and operations Are you running a dynamic business? This book shows you how!

Jossey-Bass Guides to Online Teaching and Learning Learning Online with Games, Simulations, and Virtual Worlds Strategies for Online Instruction Clark Aldrich Learning Online with Games, Simulations, and Virtual Worlds The infusion of games, simulations, and virtual worlds into online learning can be a transforming experience for both the instructor and the student. This practical guide, written by education game expert Clark Aldrich, shows faculty members and instructional designers how to identify opportunities for building games, simulations, and virtual environments into the curriculum; how to successfully incorporate these interactive environments to enhance student learning; and how to measure the learning outcomes. It also discusses how to build institutional support for using and financing more complex simulations. The book includes frameworks, tips, case studies and other real examples, and resources. Praise for Learning Online with Games, Simulations, and Virtual Worlds «Clark Aldrich provides powerful insights into the dynamic arena of games, simulations, and virtual worlds in a simultaneously entertaining and serious manner as only he can. If you are involved with educating anyone, from your own children to classrooms full of students, you need to devour this book.» – Karl Kapp, assistant director, Institute for Interactive Technologies, Bloomsburg University «At a time when the technologies for e-learning are evolving faster than most people can follow, Aldrich successfully bridges the perceptual gap between virtual worlds, digital games, and educational simulations, and provides educators with all they really need to use this technology to enhance and enrich their e-learning experiences.» – Katrin Becker, instructor, Department of Computer Science and Information Systems, Mount Royal College, and adjunct professor of education, University of Calgary «I consider this a must-read for anyone engaged in or contemplating using these tools in their classrooms or designing their own tools.» – Rick Van Sant, professor of learning and technology, Ferris State University

With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.