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Author : Gerardus Blokdyk
Publisher :
ISBN 13 : 9780655894520
Total Pages : 0 pages
Book Rating : 4.8/5 (945 download)
Download or read book Data Science Team A Complete Guide - 2019 Edition written by Gerardus Blokdyk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science Team A Complete Guide - 2019 Edition.
Author : Hadley Wickham
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491910364
Total Pages : 521 pages
Book Rating : 4.4/5 (919 download)
Download or read book R for Data Science written by Hadley Wickham and published by "O'Reilly Media, Inc.". This book was released on 2016-12-12 with total page 521 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results
Author : Gerardus Blokdyk
Publisher :
ISBN 13 : 9780655896326
Total Pages : 0 pages
Book Rating : 4.8/5 (963 download)
Download or read book Data Science Teams A Complete Guide - 2019 Edition written by Gerardus Blokdyk and published by . This book was released on with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9780655547969
Total Pages : 310 pages
Book Rating : 4.5/5 (479 download)
Download or read book Data Scientist A Complete Guide - 2019 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-06-18 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: What are some software and skills that every Data Scientist should know? Does staff have access to a wide range of open source tools, libraries, and languages to tackle analytical projects? Do you have a moral role as data scientist? How do you find data scientists? Are your data scientists evaluated against clear and defined individual and team-based performance metrics? This best-selling Data Scientist self-assessment will make you the accepted Data Scientist domain standout by revealing just what you need to know to be fluent and ready for any Data Scientist challenge. How do I reduce the effort in the Data Scientist work to be done to get problems solved? How can I ensure that plans of action include every Data Scientist task and that every Data Scientist outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Scientist costs are low? How can I deliver tailored Data Scientist advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Scientist essentials are covered, from every angle: the Data Scientist self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data Scientist outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Scientist practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Scientist are maximized with professional results. Your purchase includes access details to the Data Scientist self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Scientist Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Author : Alex Campbell
Publisher :
ISBN 13 :
Total Pages : 86 pages
Book Rating : 4.5/5 (938 download)
Download or read book Data Science for Beginners written by Alex Campbell and published by . This book was released on 2021-01-12 with total page 86 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do you wonder what the fascination is around data these days? How do we obtain insights from this data? Do you know what a data scientist does? What is artificial intelligence and machine learning? Are these the same as data science? What does it take to become a data scientist? If you have ever wondered about these questions, you have come to the right place!There are many resources and courses online that you can use to learn more about data science, but with so much information available, it can become overwhelming. One of the best ways to learn about data science is to understand different machine learning concepts, statistics, and artificial intelligence to help you design models to perform an analysis.This book has all the information you need to learn what data science is, and what the prerequisites are to become a data scientist. If you're a beginner or if you already have experience in data science, this book will have something for you.In this book, you will: Learn what data science is about.Discover the difference between data science and business intelligence.Explore the tools required for data science.Find out the technical and non-technical skills every data scientist must have.Figure out how to create a visualization of the data set with clear and easy examples.Get advice on developing a Predictive Model Using R.Uncover detailed applications of data science.And much more!The book has been structured with easy-to-understand sections to help you learn everything you need to know about data science. In this book you will learn about the prerequisites of data science and the skills you need to become a data scientist. So, what are you waiting for? Grab your copy of this comprehensive guide now
Author : Przemek Chojecki
Publisher : Przemek Chojecki
ISBN 13 :
Total Pages : 88 pages
Book Rating : 4./5 ( download)
Download or read book Data Science Job: How to become a Data Scientist written by Przemek Chojecki and published by Przemek Chojecki. This book was released on 2020-01-31 with total page 88 pages. Available in PDF, EPUB and Kindle. Book excerpt: We’re living in a digital world. Most of our global economy is digital and the sheer volume of data is stupendous. It’s 2020 and we’re living in the future. Data Scientist is one of the hottest job on the market right now. Demand for data science is huge and will only grow, and it seems like it will grow much faster than the actual number of data scientists. So if you want to make a career change and become a data scientist, now is the time. This book will guide you through the process. From my experience of working with multiple companies as a project manager, a data science consultant or a CTO, I was able to see the process of hiring data scientists and building data science teams. I know what’s important to land your first job as a data scientist, what skills you should acquire, what you should show during a job interview.
Author : Sabra Deal
Publisher :
ISBN 13 :
Total Pages : 64 pages
Book Rating : 4.7/5 (169 download)
Download or read book Data Science written by Sabra Deal and published by . This book was released on 2021-03-05 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science continues to evolve as one of the most promising and in-demand career paths for skilled professionals. Today, successful data professionals understand that they must advance past the traditional skills of analyzing large amounts of data, data mining, and programming skills. In order to uncover useful intelligence for their organizations, data scientists must master the full spectrum of the data science life cycle and possess a level of flexibility and understanding to maximize returns at each phase of the process. There are many resources and courses online that you can use to learn more about data science, but with so much information available, it can become overwhelming. One of the best ways to learn about data science is to understand different machine learning concepts, statistics, and artificial intelligence to help you design models to perform an analysis. This book has all the information you need to learn what data science is, and what the prerequisites are to become a data scientist. In this book, you will: Learn what data science is about. Discover the difference between data science and business intelligence. Explore the tools required for data science. Find out the technical and non-technical skills every data scientist must have. Figure out how to create a visualization of the data set with clear and easy examples. Get advice on developing a Predictive Model Using R. Uncover detailed applications of data science. And much more! Buy it right now!
Author : Rafael A. Irizarry
Publisher : CRC Press
ISBN 13 : 1000708039
Total Pages : 794 pages
Book Rating : 4.0/5 (7 download)
Download or read book Introduction to Data Science written by Rafael A. Irizarry and published by CRC Press. This book was released on 2019-11-20 with total page 794 pages. Available in PDF, EPUB and Kindle. Book excerpt: Introduction to Data Science: Data Analysis and Prediction Algorithms with R introduces concepts and skills that can help you tackle real-world data analysis challenges. It covers concepts from probability, statistical inference, linear regression, and machine learning. It also helps you develop skills such as R programming, data wrangling, data visualization, predictive algorithm building, file organization with UNIX/Linux shell, version control with Git and GitHub, and reproducible document preparation. This book is a textbook for a first course in data science. No previous knowledge of R is necessary, although some experience with programming may be helpful. The book is divided into six parts: R, data visualization, statistics with R, data wrangling, machine learning, and productivity tools. Each part has several chapters meant to be presented as one lecture. The author uses motivating case studies that realistically mimic a data scientist’s experience. He starts by asking specific questions and answers these through data analysis so concepts are learned as a means to answering the questions. Examples of the case studies included are: US murder rates by state, self-reported student heights, trends in world health and economics, the impact of vaccines on infectious disease rates, the financial crisis of 2007-2008, election forecasting, building a baseball team, image processing of hand-written digits, and movie recommendation systems. The statistical concepts used to answer the case study questions are only briefly introduced, so complementing with a probability and statistics textbook is highly recommended for in-depth understanding of these concepts. If you read and understand the chapters and complete the exercises, you will be prepared to learn the more advanced concepts and skills needed to become an expert.
Author : Herbert Jones
Publisher :
ISBN 13 : 9781647483043
Total Pages : 134 pages
Book Rating : 4.4/5 (83 download)
Download or read book Data Science written by Herbert Jones and published by . This book was released on 2020-01-03 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: 2 comprehensive manuscripts in 1 book Data Science: What the Best Data Scientists Know About Data Analytics, Data Mining, Statistics, Machine Learning, and Big Data - That You Don't Data Science for Business: Predictive Modeling, Data Mining, Data Analytics, Data Warehousing, Data Visualization, Regression Analysis, Database Querying
Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9780655810452
Total Pages : 316 pages
Book Rating : 4.8/5 (14 download)
Download or read book Data Science A Complete Guide - 2019 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-06-30 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to compute results with a predefined privacy budget? Are your data science teams using agile approaches (ex: DataOps) for building and deploying data products? Where does data science fit in? How well developed is the vision for Data Science in your organization? Is it sensible to pursue your organization in purely business analysis and data science? This valuable Data Science self-assessment will make you the entrusted Data Science domain assessor by revealing just what you need to know to be fluent and ready for any Data Science challenge. How do I reduce the effort in the Data Science work to be done to get problems solved? How can I ensure that plans of action include every Data Science task and that every Data Science outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Science costs are low? How can I deliver tailored Data Science advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Science essentials are covered, from every angle: the Data Science self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data Science outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Science practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Science are maximized with professional results. Your purchase includes access details to the Data Science self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Science Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Author : Steven S. Skiena
Publisher : Springer
ISBN 13 : 3319554441
Total Pages : 456 pages
Book Rating : 4.3/5 (195 download)
Download or read book The Data Science Design Manual written by Steven S. Skiena and published by Springer. This book was released on 2017-07-01 with total page 456 pages. Available in PDF, EPUB and Kindle. Book excerpt: This engaging and clearly written textbook/reference provides a must-have introduction to the rapidly emerging interdisciplinary field of data science. It focuses on the principles fundamental to becoming a good data scientist and the key skills needed to build systems for collecting, analyzing, and interpreting data. The Data Science Design Manual is a source of practical insights that highlights what really matters in analyzing data, and provides an intuitive understanding of how these core concepts can be used. The book does not emphasize any particular programming language or suite of data-analysis tools, focusing instead on high-level discussion of important design principles. This easy-to-read text ideally serves the needs of undergraduate and early graduate students embarking on an “Introduction to Data Science” course. It reveals how this discipline sits at the intersection of statistics, computer science, and machine learning, with a distinct heft and character of its own. Practitioners in these and related fields will find this book perfect for self-study as well. Additional learning tools: Contains “War Stories,” offering perspectives on how data science applies in the real world Includes “Homework Problems,” providing a wide range of exercises and projects for self-study Provides a complete set of lecture slides and online video lectures at www.data-manual.com Provides “Take-Home Lessons,” emphasizing the big-picture concepts to learn from each chapter Recommends exciting “Kaggle Challenges” from the online platform Kaggle Highlights “False Starts,” revealing the subtle reasons why certain approaches fail Offers examples taken from the data science television show “The Quant Shop” (www.quant-shop.com)
Author : Abdishakur Hassan
Publisher : Packt Publishing Ltd
ISBN 13 : 1789809339
Total Pages : 165 pages
Book Rating : 4.7/5 (898 download)
Download or read book Geospatial Data Science Quick Start Guide written by Abdishakur Hassan and published by Packt Publishing Ltd. This book was released on 2019-05-31 with total page 165 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover the power of location data to build effective, intelligent data models with Geospatial ecosystems Key FeaturesManipulate location-based data and create intelligent geospatial data modelsBuild effective location recommendation systems used by popular companies such as UberA hands-on guide to help you consume spatial data and parallelize GIS operations effectivelyBook Description Data scientists, who have access to vast data streams, are a bit myopic when it comes to intrinsic and extrinsic location-based data and are missing out on the intelligence it can provide to their models. This book demonstrates effective techniques for using the power of data science and geospatial intelligence to build effective, intelligent data models that make use of location-based data to give useful predictions and analyses. This book begins with a quick overview of the fundamentals of location-based data and how techniques such as Exploratory Data Analysis can be applied to it. We then delve into spatial operations such as computing distances, areas, extents, centroids, buffer polygons, intersecting geometries, geocoding, and more, which adds additional context to location data. Moving ahead, you will learn how to quickly build and deploy a geo-fencing system using Python. Lastly, you will learn how to leverage geospatial analysis techniques in popular recommendation systems such as collaborative filtering and location-based recommendations, and more. By the end of the book, you will be a rockstar when it comes to performing geospatial analysis with ease. What you will learnLearn how companies now use location dataSet up your Python environment and install Python geospatial packagesVisualize spatial data as graphsExtract geometry from spatial dataPerform spatial regression from scratchBuild web applications which dynamically references geospatial dataWho this book is for Data Scientists who would like to leverage location-based data and want to use location-based intelligence in their data models will find this book useful. This book is also for GIS developers who wish to incorporate data analysis in their projects. Knowledge of Python programming and some basic understanding of data analysis are all you need to get the most out of this book.
Author : Gerardus Blokdyk
Publisher :
ISBN 13 : 9780655893158
Total Pages : 0 pages
Book Rating : 4.8/5 (931 download)
Download or read book Citizen Data Science A Complete Guide - 2019 Edition written by Gerardus Blokdyk and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Citizen Data Science A Complete Guide - 2019 Edition.
Author : Gerardus Blokdyk
Publisher : 5starcooks
ISBN 13 : 9780655844532
Total Pages : 304 pages
Book Rating : 4.8/5 (445 download)
Download or read book Data Science Team A Complete Guide - 2019 Edition written by Gerardus Blokdyk and published by 5starcooks. This book was released on 2019-08-07 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Do data science teams have standardized and repeatable processes for executing analytical workflows that are documented and shared across teams? What should the next improvement project be that is related to data science team? Do you think data science team accomplishes the goals you expect it to accomplish? Risk Identification: What are the possible risk events your organization faces in relation to data science team? How do you manage data science team Knowledge Management (KM)? This valuable Data Science Team self-assessment will make you the entrusted Data Science Team domain auditor by revealing just what you need to know to be fluent and ready for any Data Science Team challenge. How do I reduce the effort in the Data Science Team work to be done to get problems solved? How can I ensure that plans of action include every Data Science Team task and that every Data Science Team outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Science Team costs are low? How can I deliver tailored Data Science Team advice instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Science Team essentials are covered, from every angle: the Data Science Team self-assessment shows succinctly and clearly that what needs to be clarified to organize the required activities and processes so that Data Science Team outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Science Team practitioners. Their mastery, combined with the easy elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Science Team are maximized with professional results. Your purchase includes access details to the Data Science Team self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows you exactly what to do next. Your exclusive instant access details can be found in your book. You will receive the following contents with New and Updated specific criteria: - The latest quick edition of the book in PDF - The latest complete edition of the book in PDF, which criteria correspond to the criteria in... - The Self-Assessment Excel Dashboard - Example pre-filled Self-Assessment Excel Dashboard to get familiar with results generation - In-depth and specific Data Science Team Checklists - Project management checklists and templates to assist with implementation INCLUDES LIFETIME SELF ASSESSMENT UPDATES Every self assessment comes with Lifetime Updates and Lifetime Free Updated Books. Lifetime Updates is an industry-first feature which allows you to receive verified self assessment updates, ensuring you always have the most accurate information at your fingertips.
Author : Howard Steven Friedman
Publisher : Columbia University Press
ISBN 13 : 0231556691
Total Pages : 271 pages
Book Rating : 4.2/5 (315 download)
Download or read book Winning with Data Science written by Howard Steven Friedman and published by Columbia University Press. This book was released on 2024-01-30 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you are a newly minted MBA or a project manager at a Fortune 500 company, data science will play a major role in your career. Knowing how to communicate effectively with data scientists in order to obtain maximum value from their expertise is essential. This book is a compelling and comprehensive guide to data science, emphasizing its real-world business applications and focusing on how to collaborate productively with data science teams. Taking an engaging narrative approach, Winning with Data Science covers the fundamental concepts without getting bogged down in complex equations or programming languages. It provides clear explanations of key terms, tools, and techniques, illustrated through practical examples. The book follows the stories of Kamala and Steve, two professionals who need to collaborate with data science teams to achieve their business goals. Howard Steven Friedman and Akshay Swaminathan walk readers through each step of managing a data science project, from understanding the different roles on a data science team to identifying the right software. They equip readers with critical questions to ask data analysts, statisticians, data scientists, and other technical experts to avoid wasting time and money. Winning with Data Science is a must-read for anyone who works with data science teams or is interested in the practical side of the subject.
Author : Stylianos Kampakis
Publisher : Apress
ISBN 13 : 1484254945
Total Pages : 154 pages
Book Rating : 4.4/5 (842 download)
Download or read book The Decision Maker's Handbook to Data Science written by Stylianos Kampakis and published by Apress. This book was released on 2019-11-26 with total page 154 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics.Become skilled at thinking like a data scientist, without being one.Discover how to hire and manage data scientists.Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.
Author : Joel Grus
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491904399
Total Pages : 336 pages
Book Rating : 4.4/5 (919 download)
Download or read book Data Science from Scratch written by Joel Grus and published by "O'Reilly Media, Inc.". This book was released on 2015-04-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data science libraries, frameworks, modules, and toolkits are great for doing data science, but they’re also a good way to dive into the discipline without actually understanding data science. In this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you have an aptitude for mathematics and some programming skills, author Joel Grus will help you get comfortable with the math and statistics at the core of data science, and with hacking skills you need to get started as a data scientist. Today’s messy glut of data holds answers to questions no one’s even thought to ask. This book provides you with the know-how to dig those answers out. Get a crash course in Python Learn the basics of linear algebra, statistics, and probability—and understand how and when they're used in data science Collect, explore, clean, munge, and manipulate data Dive into the fundamentals of machine learning Implement models such as k-nearest Neighbors, Naive Bayes, linear and logistic regression, decision trees, neural networks, and clustering Explore recommender systems, natural language processing, network analysis, MapReduce, and databases
