Fundamentals Of Data Analytics
DOWNLOAD eBooks
Download Fundamentals Of Data Analytics PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Fundamentals Of Data Analytics book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Fundamentals Of Data Analytics
DOWNLOAD eBooks
Author : Russell Dawson
language : en
Publisher: Jws Publishing
Release Date : 2023-12-20
Fundamentals Of Data Analytics written by Russell Dawson and has been published by Jws Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-20 with Computers categories.
Gain a competitive edge in today's data-driven world and build a rich career as a data professional that drives business success and innovation... Did you know that every minute, people around the world make 5.9 million searches on Google, share 1.7 million posts on Facebook, and watch 1 million hours of videos? And that's not even all of it! In total, the world creates a massive 328 million terabytes of data every day! Data is everywhere... and it has become the essential building block of this modern society, shaping the future of businesses, technology, and human interactions. It's no wonder that data professional roles, such as data analysts, data scientists, and data architects are now highly in demand in this data-driven world. And that's why now is the perfect time to pursue a career in data. But what does it take to become a competent data professional? This book has all the answers! Building a successful career in data is all about cultivating the necessary mindset, knowledge, and skills. This book is your ultimate guide to understanding the fundamentals of data analytics, helping you unlock the expertise of efficiently solving real-world data-related problems. Here is just a fraction of what you will discover: A comprehensive guide to the data analytics process - a beginner-friendly 5-step framework to kickstart your journey into analyzing and processing data How to get started with the fundamental concepts, theories, and models for accurately analyzing data Everything you ever needed to know about data mining and machine learning principles - your gateway to unlocking the secrets of data's hidden potential Why business run on a data-driven culture, and how you can leverage it using real-time business intelligence analytics Strategies and techniques to build a problem-solving mindset that can overcome any complex and unique dataset How to create compelling and dynamic visualizations that help generate insights and make data-driven decisions The 4 pillars of a new digital world - discover how emerging technologies will transform the landscape of analyzing data And much more. Believe it or not, you can be terrible in math or statistics and still pursue a career in data. Yes, you need a good grasp of the basics but always keep in mind that knowledge can be acquired and skills can be developed. The key is to not be intimidated by the strings of characters and numbers. Focus, instead, on building a mindset that thirsts for knowledge. You'll be surprised by how much you're able to do with just that. And this book is here to guide you throughout this journey, so that crunching data becomes second nature to you. So, what are you waiting for? Ready to master the fundamentals and build a successful career in data analytics?
Fundamentals Of Data Science
DOWNLOAD eBooks
Author : Sanjeev J. Wagh
language : en
Publisher: CRC Press
Release Date : 2021-09-26
Fundamentals Of Data Science written by Sanjeev J. Wagh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-26 with Business & Economics categories.
Fundamentals of Data Science is designed for students, academicians and practitioners with a complete walkthrough right from the foundational groundwork required to outlining all the concepts, techniques and tools required to understand Data Science. Data Science is an umbrella term for the non-traditional techniques and technologies that are required to collect, aggregate, process, and gain insights from massive datasets. This book offers all the processes, methodologies, various steps like data acquisition, pre-process, mining, prediction, and visualization tools for extracting insights from vast amounts of data by the use of various scientific methods, algorithms, and processes Readers will learn the steps necessary to create the application with SQl, NoSQL, Python, R, Matlab, Octave and Tablue. This book provides a stepwise approach to building solutions to data science applications right from understanding the fundamentals, performing data analytics to writing source code. All the concepts are discussed in simple English to help the community to become Data Scientist without much pre-requisite knowledge. Features : Simple strategies for developing statistical models that analyze data and detect patterns, trends, and relationships in data sets. Complete roadmap to Data Science approach with dedicatedsections which includes Fundamentals, Methodology and Tools. Focussed approach for learning and practice various Data Science Toolswith Sample code and examples for practice. Information is presented in an accessible way for students, researchers and academicians and professionals.
Fundamentals Of Data Analytics
DOWNLOAD eBooks
Author : Rudolf Mathar
language : en
Publisher: Springer Nature
Release Date : 2020-09-15
Fundamentals Of Data Analytics written by Rudolf Mathar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-15 with Mathematics categories.
This book introduces the basic methodologies for successful data analytics. Matrix optimization and approximation are explained in detail and extensively applied to dimensionality reduction by principal component analysis and multidimensional scaling. Diffusion maps and spectral clustering are derived as powerful tools. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
Fundamentals Of Data Science
DOWNLOAD eBooks
Author : Samuel Burns
language : en
Publisher:
Release Date : 2019-09-17
Fundamentals Of Data Science written by Samuel Burns and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-17 with Big data categories.
"This book is for students or anyone, with limited or no prior programming, statistics, and data analytics knowledge. This short guide is ideal for absolute beginners, or anyone who wants to acquire a basic working knowledge of data science. It is an excellent guide if you want to learn about the principals of data science from scratch, in just a few hours. The author discussed everything that you need to know about data science. First, you are guided to learn the meaning of data science. The history of data science has been discussed to help you know how people came to realize that data is a rich source of knowledge and intelligence. The theories underlying data science have been discussed. Examples include decision and estimation theories. The author discussed the various machine learning algorithms used in data science and the various steps one has to undergo when performing data science tasks, from data collection to data presentation and visualization. The author helps you to know the various ways through which you can apply data science in your business for increased profits. A simple language has been used to ensure ease of understanding, especially for beginners." --
Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition
DOWNLOAD eBooks
Author : John D. Kelleher
language : en
Publisher: MIT Press
Release Date : 2020-10-20
Fundamentals Of Machine Learning For Predictive Data Analytics Second Edition written by John D. Kelleher and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-20 with Computers categories.
The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.
Data Science Fundamentals And Practical Approaches
DOWNLOAD eBooks
Author : Dr. Gypsy Nandi
language : en
Publisher: BPB Publications
Release Date : 2020-06-02
Data Science Fundamentals And Practical Approaches written by Dr. Gypsy Nandi and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-06-02 with Computers categories.
Learn how to process and analysis data using PythonÊ KEY FEATURESÊ - The book has theories explained elaborately along with Python code and corresponding output to support the theoretical explanations. The Python codes are provided with step-by-step comments to explain each instruction of the code. - The book is not just dealing with the background mathematics alone or only the programs but beautifully correlates the background mathematics to the theory and then finally translating it into the programs. - A rich set of chapter-end exercises are provided, consisting of both short-answer questions and long-answer questions. DESCRIPTION This book introduces the fundamental concepts of Data Science, which has proved to be a major game-changer in business solving problems.Ê Topics covered in the book include fundamentals of Data Science, data preprocessing, data plotting and visualization, statistical data analysis, machine learning for data analysis, time-series analysis, deep learning for Data Science, social media analytics, business analytics, and Big Data analytics. The content of the book describes the fundamentals of each of the Data Science related topics together with illustrative examples as to how various data analysis techniques can be implemented using different tools and libraries of Python programming language. Each chapter contains numerous examples and illustrative output to explain the important basic concepts. An appropriate number of questions is presented at the end of each chapter for self-assessing the conceptual understanding. The references presented at the end of every chapter will help the readers to explore more on a given topic.Ê WHAT WILL YOU LEARNÊ Perform processing on data for making it ready for visual plot and understand the pattern in data over time. Understand what machine learning is and how learning can be incorporated into a program. Know how tools can be used to perform analysis on big data using python and other standard tools. Perform social media analytics, business analytics, and data analytics on any data of a company or organization. WHO THIS BOOK IS FOR The book is for readers with basic programming and mathematical skills. The book is for any engineering graduates that wish to apply data science in their projects or wish to build a career in this direction. The book can be read by anyone who has an interest in data analysis and would like to explore more out of interest or to apply it to certain real-life problems. TABLE OF CONTENTS 1. Fundamentals of Data Science1 2. Data Preprocessing 3. Data Plotting and Visualization 4. Statistical Data Analysis 5. Machine Learning for Data Science 6. Time-Series Analysis 7. Deep Learning for Data Science 8. Social Media Analytics 9. Business Analytics 10. Big Data Analytics
Databases Data Science And Data Analytics Fundamentals
DOWNLOAD eBooks
Author : Johnathan Mun
language : en
Publisher:
Release Date : 2020-04-27
Databases Data Science And Data Analytics Fundamentals written by Johnathan Mun and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-27 with Computers categories.
Slides for the course covering the fundamentals of databases. The material covered includes Basic SQL, IBM Cloud DB2, Microsoft Access, Microsoft Excel, Python, QDM SQL, Risk Simulator, ROV BizStats.
Data Analytics For Intelligent Transportation Systems
DOWNLOAD eBooks
Author : Mashrur Chowdhury
language : en
Publisher: Elsevier
Release Date : 2017-04-05
Data Analytics For Intelligent Transportation Systems written by Mashrur Chowdhury and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-04-05 with Business & Economics categories.
Data Analytics for Intelligent Transportation Systems provides in-depth coverage of data-enabled methods for analyzing intelligent transportation systems that includes detailed coverage of the tools needed to implement these methods using big data analytics and other computing techniques. The book examines the major characteristics of connected transportation systems, along with the fundamental concepts of how to analyze the data they produce. It explores collecting, archiving, processing, and distributing the data, designing data infrastructures, data management and delivery systems, and the required hardware and software technologies. Users will learn how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications, along with key safety and environmental applications for both commercial and passenger vehicles, data privacy and security issues, and the role of social media data in traffic planning. Includes case studies in each chapter that illustrate the application of concepts covered Presents extensive coverage of existing and forthcoming intelligent transportation systems and data analytics technologies Contains contributors from both leading academic and commercial researchers Explains how to design effective data visualizations, tactics on the planning process, and how to evaluate alternative data analytics for different connected transportation applications
Fundamentals Of Data Analytics
DOWNLOAD eBooks
Author : Prof. Dipanjan Kumar Dey
language : en
Publisher: Sankalp Publication
Release Date :
Fundamentals Of Data Analytics written by Prof. Dipanjan Kumar Dey and has been published by Sankalp Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on with Education categories.
: Data analytics help a business optimize its performance, perform more efficiently, maximize profit, or make more strategically-guided decisions. The techniques and processes of data analytics have been automated into mechanical processes and algorithms that work over raw data for human consumption. Various approaches to data analytics include looking at what happened (descriptive analytics), why something happened (diagnostic analytics), what is going to happen (predictive analytics), or what should be done next (prescriptive analytics). Data analytics relies on a variety of software tools ranging from spreadsheets, data visualization, and reporting tools, data mining programs, or open-source languages for the greatest data manipulation.
Data Analytics Principles Tools And Practices
DOWNLOAD eBooks
Author : Gaurav Aroraa
language : en
Publisher: BPB Publications
Release Date : 2022-01-24
Data Analytics Principles Tools And Practices written by Gaurav Aroraa and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-24 with Antiques & Collectibles categories.
A Complete Data Analytics Guide for Learners and Professionals. KEY FEATURES ● Learn Big Data, Hadoop Architecture, HBase, Hive and NoSQL Database. ● Dive into Machine Learning, its tools, and applications. ● Coverage of applications of Big Data, Data Analysis, and Business Intelligence. DESCRIPTION These days critical problem solving related to data and data sciences is in demand. Professionals who can solve real data science problems using data science tools are in demand. The book “Data Analytics: Principles, Tools, and Practices” can be considered a handbook or a guide for professionals who want to start their journey in the field of data science. The journey starts with the introduction of DBMS, RDBMS, NoSQL, and DocumentDB. The book introduces the essentials of data science and the modern ecosystem, including the important steps such as data ingestion, data munging, and visualization. The book covers the different types of analysis, different Hadoop ecosystem tools like Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. It also includes the different machine learning techniques that are useful for data analytics and how to visualize data with different graphs and charts. The book discusses useful tools and approaches for data analytics, supported by concrete code examples. After reading this book, you will be motivated to explore real data analytics and make use of the acquired knowledge on databases, BI/DW, data visualization, Big Data tools, and statistical science. WHAT YOU WILL LEARN ● Familiarize yourself with Apache Spark, Apache Hive, R, MapReduce, and NoSQL Database. ● Learn to manage data warehousing with real time transaction processing. ● Explore various machine learning techniques that apply to data analytics. ● Learn how to visualize data using a variety of graphs and charts using real-world examples from the industry. ● Acquaint yourself with Big Data tools and statistical techniques for machine learning. WHO THIS BOOK IS FOR IT graduates, data engineers and entry-level professionals who have a basic understanding of the tools and techniques but want to learn more about how they fit into a broader context are encouraged to read this book. TABLE OF CONTENTS 1. Database Management System 2. Online Transaction Processing and Data Warehouse 3. Business Intelligence and its deeper dynamics 4. Introduction to Data Visualization 5. Advanced Data Visualization 6. Introduction to Big Data and Hadoop 7. Application of Big Data Real Use Cases 8. Application of Big Data 9. Introduction to Machine Learning 10. Advanced Concepts to Machine Learning 11. Application of Machine Learning