Design and analyze electronic components and systems with the help of powerful software and effective skillsets. Balancing theory with practical exploration of the relevant software, you'll start solving power electronics problems like a pro. Using MATLAB®/Simulink®, you'll analyze the circuit in a laptop charger; interface with the power electronics converter controlling a washing machine's motor; turn on lamps with an electronic ballast; convert AC into DC power; and more! Power electronics are at the bedrock of all the wonderful devices simplifying our daily life. Designing them isn't just about understanding schematics. It also requires measuring twice and cutting once. In order to save time and money, a power electronics circuit must be simulated before construction. So you'll learn how to work with one of the most powerful simulation tools for this purpose. That way you'll know before you even go to make it whether the circuit works as expected. Learnto work with MATLAB®/Simulink® by directly applying and building the projects in this book. Or use it as a lab manual for power electronics and industrial electronics. Either way, using strong simulations and solid design theory, you'll be able to build power electronics that don't fail. What You'll Learn Simulate power electronics effectively before building them Select suitable semiconductor components for your circuit based on simulation waveforms Extract dynamic models of converters and design suitable controllers for them Who This Book Is For Engineers and students who want to simulate power electronics circuits in MATLAB®/Simulink®.

Master the art of workflow automation with Microsoft Power Automate using this approachable, hands-on guide. By following practical examples and step-by-step tutorials, you'll learn how to streamline your business processes with minimal coding experience. Explore key features like connectors, actions, and triggers, and apply them to real-world applications to enhance productivity. What this Book will help me do Understand the fundamental principles of Microsoft Power Automate and its utility in business process optimization. Learn to create automation flows that seamlessly integrate with Microsoft 365 applications and popular third-party services. Gain practical experience working with Power Automate Desktop for robotic process automation. Acquire knowledge of using AI tools within Power Automate, such as sentiment analysis models. Develop skills to efficiently troubleshoot, monitor, and distribute automation flows. Author(s) Aaron Guilmette is an experienced technical author and Microsoft expert. With a deep understanding of Microsoft Power Automate and the Power Platform, Aaron brings a wealth of knowledge to his teaching. He specializes in helping users transition from basic to advanced automation concepts and is known for his clear, structured, and actionable writing style. Who is it for? This book is for professionals looking to streamline their workflows and embrace automation with the Microsoft 365 suite. No extensive technical knowledge is required, making it ideal for beginners who want to learn practical workflow automation. Experienced users can also benefit from exploring advanced features like AI integrations. If you're aiming to improve productivity and reduce manual tasks, this book is perfect for you.

An indispensable guide for statistical programmers in the pharmaceutical industry. Statistical programmers in the pharmaceutical industry need to create standardized clinical data using rules created and governed by the Clinical Data Interchange Standards Consortium (CDISC). This book introduces the basic concepts, pharmaceutical industry knowledge, and SAS programming practices that every programmer needs to know to comply with regulatory requirements. Step-by-step, you will learn how data should be structured at each stage of the process from annotating electronic Case Report Forms (eCRFs) and defining the relationship between SDTM and ADaM, to understanding how to generate a Define-XML file to transmit metadata. Filled with clear explanations and example code, this book focuses only on the essential information that entry-level programmers need to succeed.

Prepare for Microsoft Exam PL-300 and help demonstrate your real-world ability to deliver actionable insights with Power BI by leveraging available data and domain expertise; to provide meaningful business value through clear data visualizations; to enable others to perform self-service analytics, and to deploy and configure solutions for consumption. Designed for data analysts, business users, and other professionals, this Exam Ref focuses on the critical thinking and decision-making acumen needed for success at the Microsoft Certified: Power BI Data Analyst Associate level. Focus on the expertise measured by these objectives: Prepare the data Model the data Visualize and analyze the data Deploy and maintain assets This Microsoft Exam Ref: Organizes its coverage by exam objectives Features strategic, what-if scenarios to challenge you Assumes you are a data analyst, business intelligence professional, report creator, or other professional seeking to validate your skills and knowledge in analyzing data with Power BI About the Exam Exam PL-300 focuses on knowledge needed to get data from different data sources; clean, transform, and load data; design and develop data models; create model calculations with DAX; optimize model performance; create reports and dashboards; enhance reports for usability and storytelling; identify patterns and trends; and manage files, datasets, and workspaces. About Microsoft Certification Passing this exam fulfills your requirements for the Microsoft Certified: Power BI Data Analyst Associate certification, demonstrating your understanding of data repositories and data processes, and your skills in designing and building scalable data models, cleaning and transforming data, enabling advanced analytic capabilities to provide meaningful business value, and collaborating with key stakeholders to deliver relevant insights based on identified business requirements. See full details at: microsoft.com/learn ...

Begin working with the Grafana data visualization platform. This book is a “how-to manual” for deploying and administering Grafana, creating real-time dashboards and alerts, exploring the data you have, and even synthesizing new data by combining and manipulating data from multiple different sources. You’ll be able to see and manage data on any scale, from your laptop or a Raspberry Pi to a production datacenter or even a multi-region cloud environment! Getting Started with Grafana takes a hands-on approach. You’ll learn by doing with easy-to-follow examples along with pointers to more resources to help you go deeper. The skills you’ll learn will help you provide business value by monitoring your operations in real time and reacting to changing circumstances as they occur. You’ll be able to derive new insights from your existing data through Grafana’s powerful and beautiful graphing capabilities, and you’ll be able to share your dashboards with colleagues soeveryone in your organization can benefit. What You Will Learn Connect to data "where it lives” and work with multiple sources of data Build beautiful and informative dashboards that show real-time status Deploy Grafana at any scale and manage it efficiently Integrate with other enterprise systems such as LDAP or Active Directory Automate creation and deployment of Grafana, dashboards, and alerts Understand what is available in the Enterprise version of Grafana Who This Book Is For Anyone who has data that they want to understand visually, IT professionals who work with multiple sources of data on a regular basis and need to make sense of the confusion that this data sprawl causes, and people who learn best by doing and want to get hands-on experience quickly with a project and then grow their knowledge

Healthcare is the next frontier for data science. Using the latest in machine learning, deep learning, and natural language processing, you'll be able to solve healthcare's most pressing problems: reducing cost of care, ensuring patients get the best treatment, and increasing accessibility for the underserved. But first, you have to learn how to access and make sense of all that data. This book provides pragmatic and hands-on solutions for working with healthcare data, from data extraction to cleaning and harmonization to feature engineering. Author Andrew Nguyen covers specific ML and deep learning examples with a focus on producing high-quality data. You'll discover how graph technologies help you connect disparate data sources so you can solve healthcare's most challenging problems using advanced analytics. You'll learn: Different types of healthcare data: electronic health records, clinical registries and trials, digital health tools, and claims data The challenges of working with healthcare data, especially when trying to aggregate data from multiple sources Current options for extracting structured data from clinical text How to make trade-offs when using tools and frameworks for normalizing structured healthcare data How to harmonize healthcare data using terminologies, ontologies, and mappings and crosswalks

Simplify data science infrastructure to give data scientists an efficient path from prototype to production. In Effective Data Science Infrastructure you will learn how to: Design data science infrastructure that boosts productivity Handle compute and orchestration in the cloud Deploy machine learning to production Monitor and manage performance and results Combine cloud-based tools into a cohesive data science environment Develop reproducible data science projects using Metaflow, Conda, and Docker Architect complex applications for multiple teams and large datasets Customize and grow data science infrastructure Effective Data Science Infrastructure: How to make data scientists more productive is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data-driven companies to manage their cutting edge data infrastructure. In it, you’ll master scalable techniques for data storage, computation, experiment tracking, and orchestration that are relevant to companies of all shapes and sizes. You’ll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python. The author is donating proceeds from this book to charities that support women and underrepresented groups in data science. About the Technology Growing data science projects from prototype to production requires reliable infrastructure. Using the powerful new techniques and tooling in this book, you can stand up an infrastructure stack that will scale with any organization, from startups to the largest enterprises. About the Book Effective Data Science Infrastructure teaches you to build data pipelines and project workflows that will supercharge data scientists and their projects. Based on state-of-the-art tools and concepts that power data operations of Netflix, this book introduces a customizable cloud-based approach to model development and MLOps that you can easily adapt to your company’s specific needs. As you roll out these practical processes, your teams will produce better and faster results when applying data science and machine learning to a wide array of business problems. What's Inside Handle compute and orchestration in the cloud Combine cloud-based tools into a cohesive data science environment Develop reproducible data science projects using Metaflow, AWS, and the Python data ecosystem Architect complex applications that require large datasets and models, and a team of data scientists About the Reader For infrastructure engineers and engineering-minded data scientists who are familiar with Python. About the Author At Netflix, Ville Tuulos designed and built Metaflow, a full-stack framework for data science. Currently, he is the CEO of a startup focusing on data science infrastructure. Quotes By reading and referring to this book, I’m confident you will learn how to make your machine learning operations much more efficient and productive. - From the Foreword by Travis Oliphant, Author of NumPy, Founder of Anaconda, PyData, and NumFOCUS Effective Data Science Infrastructure is a brilliant book. It’s a must-have for every data science team. - Ninoslav Cerkez, Logit More data science. Less headaches. - Dr. Abel Alejandro Coronado Iruegas, National Institute of Statistics and Geography of Mexico Indispensable. A copy should be on every data engineer’s bookshelf. - Matthew Copple, Grand River Analytics

A unified and systematic theoretical framework for solving problems related to finite impulse response (FIR) estimate Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches is a comprehensive investigation into batch state estimators and recursive forms. The work begins by introducing the reader to the state estimation approach and provides a brief historical overview. Next, the work discusses the specific properties of finite impulse response (FIR) state estimators. Further chapters give the basics of probability and stochastic processes, discuss the available linear and nonlinear state estimators, deal with optimal FIR filtering, and consider a limited memory batch and recursive algorithms. Other topics covered include solving the q-lag FIR smoothing problem, introducing the receding horizon (RH) FIR state estimation approach, and developing the theory of FIR state estimation under disturbances. The book closes by discussing the theory of FIR state estimation for uncertain systems and providing several applications where the FIR state estimators are used effectively. Key concepts covered in the work include: A holistic overview of the state estimation approach, which arose from the need to know the internal state of a real system, given that the input and output are both known Optimal, optimal unbiased, maximum likelihood, and unbiased and robust finite impulse response (FIR) structures FIR state estimation approach along with the infinite impulse response (IIR) and Kalman approaches Cost functions and the most critical properties of FIR and IIR state estimates Optimal and Robust State Estimation: Finite Impulse Response (FIR) and Kalman Approaches was written for professionals in the fields of microwave engineering, system engineering, and robotics who wish to move towards solving finite impulse response (FIR) estimate issues in both theoretical and practical applications. Graduate and senior undergraduate students with coursework dealing with state estimation will also be able to use the book to gain a valuable foundation of knowledge and become more adept in their chosen fields of study.

101 Career Myths Debunked is essential reading for college students, job hunters, and career changers to discover the myths holding them back and reveal the surprising truths and practical steps that will set them on the path to career success.

Doing Statistical Analysis looks at three kinds of statistical research questions – descriptive, associational and inferential – and shows students how to conduct statistical analyses and interpret the results.

Microsoft Power Platform Solution Architect's Handbook is your definitive resource for mastering Enterprise-grade solution architecture using Microsoft Power Platform. By covering both practical examples and theoretical best practices, this book ensures you are well-prepared to tackle real-world challenges and excel in the PL-600 certification exam. What this Book will help me do Master the essential practices of solution architecture for optimal design. Develop secure integrations and data strategies for cutting-edge applications. Learn sophisticated lifecycle and compliance management using Azure DevOps. Build impactful, compliant, and flexible solutions using Power Platform. Prepare effectively for the PL-600 certification exam and excel in your field. Author(s) Hugo Herrera is a respected technology expert specializing in solution architecture and enterprise-grade IT solutions, particularly with Microsoft Power Platform. Drawing from years of experience, Hugo emphasizes practical, actionable strategies to elevate professionals. Through this book, Hugo shares his deep expertise and makes complex concepts accessible. Who is it for? This book is perfect for solution architects, enterprise architects, IT consultants, and analysts focused on Microsoft Power Platform and related technologies. It provides insight and tools for professionals looking to enhance their competencies, advance their careers, and prepare for the PL-600 exam. The reader should have a solid understanding of Power Platform fundamentals.

API Strategy for Decision Makers provides actionable best practices for building winning API products. Whether you're with an API-first company or with an existing enterprise software company looking to expand your API offerings, this report shows you how to grow your API product into a center of revenue and metrics to measure against. Authors Mike Amundsen and Derric Gilling draw on real-life examples to guide you through the important considerations for successfully developing and executing on your API strategy. By identifying winning business cases, sharing best practices for adoption and monetization, and showing you how to create a great API experience, this report presents a detailed overview for every C-suite executive and product owner managing an API platform. With this report, you'll: Learn how to apply common product management techniques to better manage your APIs as products Discover how to define a strategy from initial adoption, monetization, and deprecation of your APIs Determine how to position your API products in your company's portfolio as well as the wider market Dig deep into the step-by-step process of making your API strategy come to life Explore the power of API observability, monitoring, and analytics as a means to quantify, track, and optimize your API strategy

Produce high-quality, visually attractive analysis quickly and effectively with Microsoft’s key BI tool. This book teaches analysts, managers, power users, and developers how to harness the power of Microsoft’s self-service business intelligence flagship product to deliver compelling and interactive insight with remarkable ease. It then shows you the essential techniques needed to go from source data to dashboards that seize your audience’s attention and provide them with clear and accurate information. As well as producing elegant and visually arresting output, you learn how to enhance the user experience through adding polished interactivity. This book shows you how to make interactive dashboards that allow you to guide users through the meaning of the data that they are exploring. Drill down features are also covered that allow you and your audience to dig deeper and uncover new insights by exploring anomalous and interesting data points. Reading this book builds your skills around creating meaningful and elegant dashboards using a range of compelling visuals. It shows you how to apply simple techniques to convert data into business insight. The book covers tablet and smartphone layouts for delivering business value in today’s highly mobile world. You’ll learn about formatting for effect to make your data tell its story, and you’ll be a master at creating visually arresting output on multiple devices that grabs attention, builds influence, and drives change. What You Will Learn Produce designer output that will astound your bosses and peers Make new insights as you chop and tweak your data as never before Create high-quality analyses in record time Create interdependent charts, maps, and tables Deliver visually stunning information Drill down through data to provide unique understandings Outshinecompeting products and enhance existing skills Adapt your dashboard delivery to mobile devices Who This Book Is For For any Power BI user who wants to strengthen their ability to deliver compelling analytics via Microsoft’s widely adopted analytics platform. For those new to Power BI who want to learn the full extent of what the platform is capable of. For power users such as BI analysts, data architects, IT managers, accountants, and C-suite members who want to drive change in their organizations.

Dive deep into Microsoft Power BI with the second edition of 'Mastering Microsoft Power BI'. This comprehensive book equips you with the skills to transform business data into actionable insights using Power BI's latest features and techniques. From efficient data retrieval and transformation processes to creating interactive dashboards that tell impactful data stories, you will learn actionable knowledge every step of the way. What this Book will help me do Learn to master data collection and modeling using the Power Query M language Gain expertise in designing DirectQuery, import, and composite data models Understand how to create advanced analytics reports using DAX and Power BI visuals Learn to manage the Power BI environment as an administrator with Premium capacity Develop insightful, scalable, and visually impactful dashboards and reports Author(s) Greg Deckler, a seasoned Power BI expert and solution architect, and None Powell, an experienced BI consultant and data visualization specialist, bring their extensive practical knowledge to this book. Together, they share their real-world expertise and proven techniques applying Power BI's diverse capabilities. Who is it for? This book is ideal for business intelligence professionals and intermediate Power BI users. If you're looking to master data visualization, prepare insightful dashboards, and explore Power BI's full potential, this is for you. Basic understanding of BI concepts and familiarity with Power BI will ensure you get the most value.

BIG DATA ANALYTICS AND MACHINE INTELLIGENCE IN BIOMEDICAL AND HEALTH INFORMATICS Provides coverage of developments and state-of-the-art methods in the broad and diversified data analytics field and applicable areas such as big data analytics, data mining, and machine intelligence in biomedical and health informatics. The novel applications of Big Data Analytics and machine intelligence in the biomedical and healthcare sector is an emerging field comprising computer science, medicine, biology, natural environmental engineering, and pattern recognition. Biomedical and health informatics is a new era that brings tremendous opportunities and challenges due to the plentifully available biomedical data and the aim is to ensure high-quality and efficient healthcare by analyzing the data. The 12 chapters in??Big Data Analytics and Machine Intelligence in Biomedical and Health Informatics??cover the latest advances and developments in health informatics, data mining, machine learning, and artificial intelligence. They have been organized with respect to the similarity of topics addressed, ranging from issues pertaining to the Internet of Things (IoT) for biomedical engineering and health informatics, computational intelligence for medical data processing, and Internet of Medical Things??(IoMT). New researchers and practitioners working in the field will benefit from reading the book as they can quickly ascertain the best performing methods and compare the different approaches. Audience Researchers and practitioners working in the fields of biomedicine, health informatics, big data analytics, Internet of Things, and machine learning.

THE GUIDE FOR ANYONE AFRAID TO LEARN STATISTICS & ANALYTICS UPDATED WITH NEW EXAMPLES & EXERCISES This book discusses statistics and analytics using plain language and avoiding mathematical jargon. If you thought you couldn't learn these data analysis subjects because they were too technical or too mathematical, this book is for you! This edition delivers more everyday examples and end-of-chapter exercises and contains updated instructions for using Microsoft Excel. You'll use downloadable data sets and spreadsheet solutions, template-based solutions you can put right to work. Using this book, you will understand the important concepts of statistics and analytics, including learning the basic vocabulary of these subjects. Create tabular and visual summaries and learn to avoid common charting errors Gain experience working with common descriptive statistics measures including the mean, median, and mode; and standard deviation and variance, among others Understand the probability concepts that underlie inferential statistics Learn how to apply hypothesis tests, using Z, t, chi-square, ANOVA, and other techniques Develop skills using regression analysis, the most commonly-used Inferential statistical method Explore results produced by predictive analytics software Choose the right statistical or analytic techniques for any data analysis task Optionally, read the Equation Blackboards, designed for readers who want to learn about the mathematical foundations of selected methods ...

Examine select retail business scenarios to learn basic mathematics, as well as probability and statistics required to analyze big data. This book focuses on useful and imperative applied analytics needed to build a retail business and explains mathematical concepts essential for decision making and communication in retail business environments. Everyone is a buyer or seller of products these days whether through a physical department store, Amazon, or their own business website. This book is a step-by-step guide to understanding and managing the mechanics of markups, markdowns, and basic statistics, math and computers that will help in your retail business. You'll tackle what to do with data once it is has accumulated and see how to arrange the data using descriptive statistics, primarily means, median, and mode, and then how to read the corresponding charts and graphs. Analytics for Retail is your path to creating visualrepresentations that powerfully communicate information and drive decisions. What You'll Learn Review standard statistical concepts to enhance your understanding of retail data Understand the concepts of markups, markdowns and profit margins, and probability Conduct an A/B testing email campaign with all the relevant analytics calculated and explained Who This Book Is For This is a primer book for anyone in the field of retail that needs to learn or refresh their skills or for a reader who wants to move in their company to a more analytical position.

This book is your ultimate companion to mastering Microsoft Power BI and becoming proficient in data analysis and visualization. With a focus on understanding and utilizing Power BI to its fullest extent, this guide also prepares you comprehensively for the PL-300 certification exam. You will go from the basics to advanced techniques enabling you to confidently analyze and present data. What this Book will help me do Understand and connect to various data sources using Power BI. Gain skills in transforming and preparing data for advanced analysis. Develop expertise in designing and optimizing data models. Learn to create insightful reports and dashboards to convey information clearly. Prepare for and succeed in the PL-300 certification exam with practice questions. Author(s) Authors None Edenfield and None Corcoran bring extensive experience in business intelligence and data analytics to this book. They have years of hands-on expertise with Power BI and a passion for teaching analytics in a practical and accessible way. Together, they aim to empower readers to master Power BI and achieve their certification goals. Who is it for? This book is perfect for data analysts, business intelligence professionals, and anyone aiming to deepen their knowledge of Microsoft Power BI. Beginners will find approachable content to quickly get started while experienced users will find detailed topics to refine their expertise. By covering exam preparation and practical applications, this guide benefits a wide range of learners who wish to get certified and excel in data-centric roles.

Discover how to leverage the full potential of Domo, a robust cloud-based business intelligence platform, in your organization. This comprehensive guide walks you through data integration, transformation, visualization, and governance techniques, enabling you to deliver impactful, data-driven results quickly and effectively. What this Book will help me do Understand and utilize Domo's cloud data architecture for comprehensive data analysis. Seamlessly acquire and manage data using Domo connectors and tools. Create and customize dashboards that communicate data insights effectively. Build and deploy Python applications and machine learning models on Domo. Securely govern your organization's data with robust Domo features. Author(s) The author, None Burtenshaw, is an expert in business intelligence and data platforms. With years of experience working with data integration tools, their writing combines technical thoroughness with practical insights. They aim to empower professionals with the skills to excel in data-driven decision making, reflecting their passion for making technology accessible and actionable. Who is it for? This book is ideal for business intelligence professionals, including developers and analysts, looking to elevate their understanding of Domo. It is suited for those with a fundamental knowledge of data platforms seeking advanced skills in data management and visualization. BI managers will gain insights into governance and security, while analysts will find inspiration for data storytelling. If you're aiming to master the possibilities of Domo, this book is for you.

The Pandas Workshop offers a detailed journey into the world of data analysis using Python and the pandas library. Throughout the book, you'll build skills in accessing, transforming, visualizing, and modeling data, all while focusing on real-world data science challenges. You will gain the knowledge and confidence needed to dissect and derive insights from complex datasets. What this Book will help me do Understand how to access and load data from various formats including databases and web-based sources. Manipulate and transform data for analysis using efficient pandas techniques. Create insightful visualizations using Matplotlib integrated with pandas for clearer data presentation. Build predictive and descriptive data models and glean data-driven insights. Handle and analyze time-series data to uncover trends and seasonal effects in data patterns. Author(s) Blaine Bateman, Saikat Basak, Thomas Joseph, and William So collectively bring diverse expertise in data analysis, programming, and teaching. Their goal is to make cutting-edge data science techniques accessible through clear explanations and practical exercises, helping learners from varied backgrounds master the pandas library. Who is it for? This book is best suited for novice to intermediate programmers and data enthusiasts who are already familiar with Python but are new to the pandas library. Ideal readers are those interested in honing their skills in data analysis and visualization, as well as leveraging data for informed decision-making. Whether you're an analyst, aspiring data scientist, or business professional seeking to strengthen your analytical toolkit, this book provides beneficial insights and techniques.

A thought-provoking and startlingly insightful reworking of the science of prediction In Prediction Revisited: The Importance of Observation, a team of renowned experts in the field of data-driven investing delivers a ground-breaking reassessment of the delicate science of prediction for anyone who relies on data to contemplate the future. The book reveals why standard approaches to prediction based on classical statistics fail to address the complexities of social dynamics, and it provides an alternative method based on the intuitive notion of relevance. The authors describe, both conceptually and with mathematical precision, how relevance plays a central role in forming predictions from observed experience. Moreover, they propose a new and more nuanced measure of a prediction’s reliability. Prediction Revisited also offers: Clarifications of commonly accepted but less commonly understood notions of statistics Insight into the efficacy of traditional prediction models in a variety of fields Colorful biographical sketches of some of the key prediction scientists throughout history Mutually supporting conceptual and mathematical descriptions of the key insights and methods discussed within With its strikingly fresh perspective grounded in scientific rigor, Prediction Revisited is sure to earn its place as an indispensable resource for data scientists, researchers, investors, and anyone else who aspires to predict the future from the data-driven lessons of the past.

R is the most powerful tool you can use for statistical analysis. This definitive guide smooths R’s steep learning curve with practical solutions and real-world applications for commercial environments. In R in Action, Third Edition you will learn how to: Set up and install R and RStudio Clean, manage, and analyze data with R Use the ggplot2 package for graphs and visualizations Solve data management problems using R functions Fit and interpret regression models Test hypotheses and estimate confidence Simplify complex multivariate data with principal components and exploratory factor analysis Make predictions using time series forecasting Create dynamic reports and stunning visualizations Techniques for debugging programs and creating packages R in Action, Third Edition makes learning R quick and easy. That’s why thousands of data scientists have chosen this guide to help them master the powerful language. Far from being a dry academic tome, every example you’ll encounter in this book is relevant to scientific and business developers, and helps you solve common data challenges. R expert Rob Kabacoff takes you on a crash course in statistics, from dealing with messy and incomplete data to creating stunning visualizations. This revised and expanded third edition contains fresh coverage of the new tidyverse approach to data analysis and R’s state-of-the-art graphing capabilities with the ggplot2 package. About the Technology Used daily by data scientists, researchers, and quants of all types, R is the gold standard for statistical data analysis. This free and open source language includes packages for everything from advanced data visualization to deep learning. Instantly comfortable for mathematically minded users, R easily handles practical problems without forcing you to think like a software engineer. About the Book R in Action, Third Edition teaches you how to do statistical analysis and data visualization using R and its popular tidyverse packages. In it, you’ll investigate real-world data challenges, including forecasting, data mining, and dynamic report writing. This revised third edition adds new coverage for graphing with ggplot2, along with examples for machine learning topics like clustering, classification, and time series analysis. What's Inside Clean, manage, and analyze data Use the ggplot2 package for graphs and visualizations Techniques for debugging programs and creating packages A complete learning resource for R and tidyverse About the Reader Requires basic math and statistics. No prior experience with R needed. About the Author Dr. Robert I Kabacoff is a professor of quantitative analytics at Wesleyan University and a seasoned data scientist with more than 20 years of experience. Quotes Kabacoff has outdone himself by significantly improving on the already excellent previous edition. - Alain Lompo, ISO-Gruppe R in Action has been my go-to reference on R for years. The third edition contains timely updates on the tidyverse and other new tools. I would recommend this book without hesitation. - Daniel Kenney-Jung MD, Department of Pediatrics, Duke University Outstandingly well-written. The best book on R programming that I have ever read. - Kelvin Meeks, International Technology Ventures Takes the reader through a series of essential methods from basic to complex. The only R book you will ever need. - Martin Perry, Microsoft

Explore the comprehensive world of data science with "Building Data Science Solutions with Anaconda." This book covers essential topics like managing environments with Anaconda, detecting and overcoming bias, and ensuring model interpretability. Delve into practical tools and solutions, all explained in an approachable way to help you become proficient in data science workflows. What this Book will help me do Master environment management for data science projects using Anaconda and conda. Detect and mitigate dataset biases to ensure fair and ethical machine learning models. Learn advanced data science techniques with tools like NumPy, pandas, and Jupyter Notebooks. Understand and explain your machine learning models using LIME and SHAP. Grow your expertise in selecting and fine-tuning AI/ML algorithms for diverse applications. Author(s) None Meador combines extensive expertise in data science with a thorough understanding of Anaconda tools and open source software. With a background in engineering and AI model management, None provides an insightful perspective on the field. Their practical and analogy-driven approach makes technical concepts accessible to learners of any level. Who is it for? This book is ideal for data analysts, aspiring machine learning engineers, and data science professionals who wish to deepen their knowledge and make the most of Anaconda's capabilities. A prior understanding of Python and basic data science principles is assumed. If you're looking to optimize your data science workflows and gain hands-on practice, this book is for you.

Take a concise approach to learning how DAX, the function language of Power BI and PowerPivot, works. This book focuses on explaining the core concepts of DAX so that ordinary folks can gain the skills required to tackle complex data analysis problems. But make no mistake, this is in no way an introductory book on DAX. A number of the topics you will learn, such as the concepts of context transition and table expansion, are considered advanced and challenging areas of DAX. While there are numerous resources on DAX, most are written with developers in mind, making learning DAX appear an overwhelming challenge, especially for those who are coming from an Excel background or with limited coding experience. The reality is, to hit the ground running with DAX, it’s not necessary to wade through copious pages on rarified DAX functions and the technical aspects of the language. There are just a few mandatory concepts that must be fully understood before DAX can be mastered. Knowledge of everything else in DAX is built on top of these mandatory aspects. Author Alison Box has been teaching and working with DAX for over eight years, starting with DAX for PowerPivot, the Excel add-in, before moving into the Power BI platform. The guide you hold in your hands is an outcome of these years of experience explaining difficult concepts in a way that people can understand. Over the years she has refined her approach, distilling down the truth of DAX which is “you can take people through as many functions as you like, but it’s to no avail if they don’t truly understand how it all works.” You will learn to use DAX to gain powerful insights into your data by generating complex and challenging business intelligence calculations including, but not limited to: Calculations to control the filtering of information to gain better insight into the data that matters to you Calculations across dates such as comparing data for thesame period last year or the previous period Finding rolling averages and rolling totals Comparing data against targets and KPIs or against average and maximum values Using basket analysis, such as “of customers who bought product X who also bought product Y” Using “what if” analysis and scenarios Finding “like for like” sales Dynamically showing TopN/BottomN percent of customers or products by sales Finding new and returning customers or sales regions in each month or each year Who This Book Is For Excel users and non-technical users of varying levels of ability or anyone who wants to learn DAX for Power BI but lacks the confidence to do so

Discover how to enhance your data analysis with 'Artificial Intelligence with Power BI,' a resource designed to teach you how to leverage Power BI's AI capabilities. You will learn practical methods for enriching your analytics with forecasting, anomaly detection, and machine learning, equipping you to create intelligent, insightful BI reports. What this Book will help me do Learn how to apply AI capabilities such as forecasting and anomaly detection to enrich your reports and drive actionable insights. Explore data preparation techniques optimized for AI, ensuring your datasets are structured for advanced analytics. Develop skills to integrate Azure Machine Learning and Cognitive Services into Power BI, expanding your analytical toolset. Understand how to build Q&A interfaces and integrate Natural Language Processing into your BI solutions. Gain expertise in training and deploying your own machine learning models to achieve tailored insights and predictive analytics. Author(s) None Diepeveen is an experienced data analyst and Power BI expert with a passion for making advanced analytics accessible to professionals. With years of hands-on experience working in the data analytics field, they deliver insights using intuitive, practical approaches through clear and engaging tutorials. Who is it for? This book is ideal for data analysts and BI developers who aim to expand their analytics capabilities with AI. Readers should already be familiar with Power BI and are looking for a resource to teach them how to incorporate predictive and advanced AI techniques into their reporting workflow. Whether you're seeking to gain a professional edge or enhance your organization's data storytelling and insights, this guide is perfect for you.