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Author: Janani Sathish
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 364
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Book Description
Data science has taken the planet by storm. Every field of study and area of business has been affected as people increasingly realize the worth of the incredible quantities of knowledge being generated. But to extract value from those data, one must be trained within the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it a useful tool for data scientists round the world. This book is about the basics of R programming. you'll start with the fundamentals of the language, find out how to control datasets, the way to write functions, and the way to debug and optimize code. With the basics provided during this book, you'll have a solid foundation on which to create your data science toolbox. during this book you'll learn what you would like to understand to start assembling and leading a knowledge science enterprise, albeit you've got never worked in data science before. You'll get a crash program in data science in order that you'll be familiar with the sector and understand your role as a pacesetter . You'll also find out how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the info science pipeline, the goals of every stage, and the way to stay your team on track throughout. Finally, you'll learn some down-to-earth practical skills which will assist you overcome the common challenges that regularly derail data science projects Reproducibility is that the concept data analyses should be published or made available with their data and software code in order that others may verify the findings and repose on them.
Author: Janani Sathish
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 364
Get Book Here
Book Description
Data science has taken the planet by storm. Every field of study and area of business has been affected as people increasingly realize the worth of the incredible quantities of knowledge being generated. But to extract value from those data, one must be trained within the proper data science skills. The R programming language has become the de facto programming language for data science. Its flexibility, power, sophistication, and expressiveness have made it a useful tool for data scientists round the world. This book is about the basics of R programming. you'll start with the fundamentals of the language, find out how to control datasets, the way to write functions, and the way to debug and optimize code. With the basics provided during this book, you'll have a solid foundation on which to create your data science toolbox. during this book you'll learn what you would like to understand to start assembling and leading a knowledge science enterprise, albeit you've got never worked in data science before. You'll get a crash program in data science in order that you'll be familiar with the sector and understand your role as a pacesetter . You'll also find out how to recruit, assemble, evaluate, and develop a team with complementary skill sets and roles. You'll learn the structure of the info science pipeline, the goals of every stage, and the way to stay your team on track throughout. Finally, you'll learn some down-to-earth practical skills which will assist you overcome the common challenges that regularly derail data science projects Reproducibility is that the concept data analyses should be published or made available with their data and software code in order that others may verify the findings and repose on them.
Author: Simplilearn
Publisher: IndraStra Whitepapers
ISBN:
Category : Computers
Languages : en
Pages : 25
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Book Description
Data analytics is increasingly becoming a key element in shaping a company’s business strategy. Today, data influences every decision made by an organization, and this is driving the wide-scale adoption of data analytics, including machine learning technologies and artificial intelligence solutions. The heightened focus is propelling a surge in data analytics spending, reflected in various studies conducted by leading market research firms. The field of data analytics offers some amazing salaries and is not only the hottest IT job, but it is also one of the best-paying jobs in the world. This guide aims at providing the readers with everything they need to know about the data analytics field, basic terminologies, key concepts, real-life use cases, skills you must master in order to scale up your career, and training and certifications you might need to reach your dream job.
Author: Hadley Wickham
Publisher: "O'Reilly Media, Inc."
ISBN: 1491910364
Category : Computers
Languages : en
Pages : 521
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Book Description
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: Joel Grus
Publisher: "O'Reilly Media, Inc."
ISBN: 1491904399
Category : Computers
Languages : en
Pages : 408
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Book Description
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
Author: Max Datawise
Publisher: Independently Published
ISBN:
Category : Computers
Languages : en
Pages : 0
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Book Description
Attention: Are you ready to dive into the dynamic world of data analytics? Whether you're a novice eager to break into the field or a professional looking to sharpen your skills, this comprehensive guide is your ticket to mastering data analytics and catapulting your career to new heights! Interest: Unlock the secrets of data analytics with clear, step-by-step instructions that cover everything from the basics to advanced techniques. Learn how to harness the power of data to make informed decisions, drive innovation, and stay ahead of the curve in today's data-driven landscape. Discover how top companies use data to transform their operations and how you can do the same. Desire: Imagine having the confidence and skills to tackle complex data challenges, create stunning visualizations, and derive actionable insights that can revolutionize businesses. With our guide, you will gain hands-on experience with the latest tools and techniques, from Python programming to machine learning and big data technologies. Elevate your expertise and become an indispensable asset in any industry. Action: Don't wait another day to start your journey into the exciting realm of data analytics. Get your copy of "Beginner's Guide to Data Analytics: Launch Your Career with Core Competencies and Future Insights" now, and take the first step towards a rewarding and lucrative career. Embrace the future, master essential skills, and unlock endless possibilities. Start your data analytics adventure today!
Author: Kathi Dunklin
Publisher:
ISBN:
Category :
Languages : en
Pages : 188
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Book Description
As the process of analyzing raw data to find trends and answer questions, the definition of data analysis captures the wide range of the field. Whether you are a beginner or an experienced person, mastering your data analysis skills is always a challenge. You want to learn about data analysis but can't find a book with the right computer concept distribution, Or you are trying to improve your data analysis skills but want interesting examples taste with them? This book here is for you Here are some key features of this book. -Emphasis on practical examples and how the advanced techniques described in the chapters can be used in real-life to improve clarity and understanding. -Various topics such as sophisticated algorithms or even the Euclidean Square Estimate are approached in a way that the reader can understand the very basics of it and then be introduced to the technical jargon. -This ensures that the reader does not get lost in all of the mathematical and statistical words. -Efficient demonstration of almost every practical topic with the use of Python so that the readers can recreate the projects by themselves. If you're interested in taking a journey through the realms of advanced data analytic, this book is very suitable for you. Buy it right now
Author: Joseph Conley
Publisher: Orange Education Pvt Ltd
ISBN: 8197081891
Category : Computers
Languages : en
Pages : 268
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Book Description
Master the Fundamentals of Data Analytics at Scale KEY FEATURES ● Comprehensive guide to constructing data engineering workflows spanning diverse data sources ● Expert techniques for transforming and visualizing data to extract actionable insights ● Advanced methodologies for analyzing data and employing machine learning to uncover intricate patterns DESCRIPTION Embark on a transformative journey into the realm of data analytics with AWS with this practical and incisive handbook. Begin your exploration with an insightful introduction to the fundamentals of data analytics, setting the stage for your AWS adventure. The book then covers collecting data efficiently and effectively on AWS, laying the groundwork for insightful analysis. It will dive deep into processing data, uncovering invaluable techniques to harness the full potential of your datasets. The book will equip you with advanced data analysis skills, unlocking the ability to discern complex patterns and insights. It covers additional use cases for data analysis on AWS, from predictive modeling to sentiment analysis, expanding your analytical horizons. The final section of the book will utilize the power of data virtualization and interaction, revolutionizing the way you engage with and derive value from your data. Gain valuable insights into emerging trends and technologies shaping the future of data analytics, and conclude your journey with actionable next steps, empowering you to continue your data analytics odyssey with confidence. WHAT WILL YOU LEARN ● Construct streamlined data engineering workflows capable of ingesting data from diverse sources and formats. ● Employ data transformation tools to efficiently cleanse and reshape data, priming it for analysis. ● Perform ad-hoc queries for preliminary data exploration, uncovering initial insights. ● Utilize prepared datasets to craft compelling, interactive data visualizations that communicate actionable insights. ● Develop advanced machine learning and Generative AI workflows to delve into intricate aspects of complex datasets, uncovering deeper insights. WHO IS THIS BOOK FOR? This book is ideal for aspiring data engineers, analysts, and data scientists seeking to deepen their understanding and practical skills in data engineering, data transformation, visualization, and advanced analytics. It is also beneficial for professionals and students looking to leverage AWS services for their data-related tasks. TABLE OF CONTENTS 1. Introduction to Data Analytics and AWS 2. Getting Started with AWS 3. Collecting Data with AWS 4. Processing Data on AWS 5. Descriptive Analytics on AWS 6. Advanced Data Analysis on AWS 7. Additional Use Cases for Data Analysis 8. Data Visualization and Interaction on AWS 9. The Future of Data Analytics 10. Conclusion and Next Steps Index
Author: Gloria Butac
Publisher:
ISBN:
Category :
Languages : en
Pages : 188
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Book Description
As the process of analyzing raw data to find trends and answer questions, the definition of data analysis captures the wide range of the field. Whether you are a beginner or an experienced person, mastering your data analysis skills is always a challenge. You want to learn about data analysis but can't find a book with the right computer concept distribution, Or you are trying to improve your data analysis skills but want interesting examples taste with them? This book here is for you Here are some key features of this book. -Emphasis on practical examples and how the advanced techniques described in the chapters can be used in real-life to improve clarity and understanding. -Various topics such as sophisticated algorithms or even the Euclidean Square Estimate are approached in a way that the reader can understand the very basics of it and then be introduced to the technical jargon. -This ensures that the reader does not get lost in all of the mathematical and statistical words. -Efficient demonstration of almost every practical topic with the use of Python so that the readers can recreate the projects by themselves. If you're interested in taking a journey through the realms of advanced data analytic, this book is very suitable for you. Buy it right now
Author: Oliver Theobald
Publisher:
ISBN: 9781081762469
Category :
Languages : en
Pages : 88
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Book Description
While exposure to data has become more or less a daily ritual for the rank-and-file knowledge worker, true understanding-treated in this book as data literacy-resides in knowing what lies behind the data. Everything from the data's source to the specific choice of input variables, algorithmic transformations, and visual representation shape the accuracy, relevance, and value of the data and mark its journey from raw data to business insight. It's also important to grasp the terminology and basic concepts of data analytics as much as it is to have the financial literacy to be successful as a decisionmaker in the business world. In this book, we make sense of data analytics without the assumption that you understand specific data science terminology or advanced programming languages to set you on your path. Topics covered in this book: Data Mining Big Data Machine Learning Alternative Data Data Management Web Scraping Regression Analysis Clustering Analysis Association Analysis Data Visualization Business Intelligence
Author: Tech World
Publisher: Createspace Independent Publishing Platform
ISBN: 9781547016280
Category : Big data
Languages : en
Pages : 0
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Book Description
DATA ANALYTICS FOR BEGINNERS Are you ready to discover why data analytics is the only hope for fact based decisions? Would you like learn how insightful-driven decisions can help organizations manage their strategic, operation and financial performance that can help them increase their shareholder value? This book explores all the concepts about data analytics that can help any beginner to master data analytics and its applications in several industries. Chapter one provides an overview of data analytics where the foundations of data analytics are explained in details. If you want to get started right away, you'll also learn the requirements for data scientists in this chapter. In chapter two, a detailed discourse on conducting analytic data research is provided to give you a big picture view of how data analytics is done. In chapter three, descriptive statistics is explored where you'll learn measures of central tendency and measures of dispersion. Chapter four reviews all the charts and graphs that you can use to communicate your analytic results. In chapter five, you'll learn the applications of data analysis in organizations. Finally, in chapter six, you'll learn some of the valuable tools that can help you advance your professional career in data analytics. You'll also learn why smart contracts are emerging as the next technologies for smart data analysis. Take action today and discover the power of Data AnalyticsDOWNLOAD YOUR COPY TODAY
