What Is Data Science
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Data Science For Beginners
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Author : Alex Campbell
language : en
Publisher:
Release Date : 2021-01-12
Data Science For Beginners written by Alex Campbell and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-12 with categories.
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
Data Science Fundamentals And Practical Approaches
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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
Data Science And Its Applications
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Author : Aakanksha Sharaff
language : en
Publisher: CRC Press
Release Date : 2021-08-17
Data Science And Its Applications written by Aakanksha Sharaff and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-17 with Computers categories.
The term "data" being mostly used, experimented, analyzed, and researched, "Data Science and its Applications" finds relevance in all domains of research studies including science, engineering, technology, management, mathematics, and many more in wide range of applications such as sentiment analysis, social medial analytics, signal processing, gene analysis, market analysis, healthcare, bioinformatics etc. The book on Data Science and its applications discusses about data science overview, scientific methods, data processing, extraction of meaningful information from data, and insight for developing the concept from different domains, highlighting mathematical and statistical models, operations research, computer programming, machine learning, data visualization, pattern recognition and others. The book also highlights data science implementation and evaluation of performance in several emerging applications such as information retrieval, cognitive science, healthcare, and computer vision. The data analysis covers the role of data science depicting different types of data such as text, image, biomedical signal etc. useful for a wide range of real time applications. The salient features of the book are: Overview, Challenges and Opportunities in Data Science and Real Time Applications Addressing Big Data Issues Useful Machine Learning Methods Disease Detection and Healthcare Applications utilizing Data Science Concepts and Deep Learning Applications in Stock Market, Education, Behavior Analysis, Image Captioning, Gene Analysis and Scene Text Analysis Data Optimization Due to multidisciplinary applications of data science concepts, the book is intended for wide range of readers that include Data Scientists, Big Data Analysists, Research Scholars engaged in Data Science and Machine Learning applications.
Big Data And Data Science
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Author : Dhaanyalakshmi Ahuja
language : en
Publisher: Educohack Press
Release Date : 2025-01-03
Big Data And Data Science written by Dhaanyalakshmi Ahuja and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-03 with Computers categories.
Big Data and Data Science: Analytics for the Future dives into the fundamentals of big data and data science. We explain the data science life cycle and its major components, such as statistics and visualization, using various programming languages like R. As technology evolves, the significance of data science and big data analytics continues to grow, making this field increasingly important. Our book is designed in a reader-friendly manner, targeting newcomers to data science. Concepts are presented clearly and can be easily implemented through the procedures and algorithms provided. As data collection multiplies exponentially, analytics remains an evolving field with vast career opportunities. We cater to two types of readers: those skeptical about the benefits of big data and predictive analytics, and enthusiasts keen to explore current applications of these technologies. Big data is a fantastic choice for launching a career in IT, and this book equips you with the knowledge needed to succeed. We cover a broad spectrum of topics, ensuring a strong foundation in data science and big data analytics.
Data Science Workflow For Beginners
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Author : Alejandro Garcia
language : en
Publisher: Alejandro Garcia
Release Date :
Data Science Workflow For Beginners written by Alejandro Garcia and has been published by Alejandro Garcia this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
This book brings to you a simple yet effective 40 to 60 mins introduction that will clear all your doubts about Data Sience and will answer some important questions like: What is data Science ? The book explores all the initial concepts a person might want to know about the data science workflow. There’s not coding, math or statistics required to successfully understand the goals and end results of this process. This book takes you on an exclusive tour of datasets and sites to download your first datasets. Then jumps into a comprehensive and easy-to-follow data science process letting you go through 3 data visualization projects. (Python Code Understanding is Recommended for the Data Visualization projects) - 40 to 60 mins reading time. - 3 Data Visualization projects. - 10 Datasets sources. - 26 Quality datasets for your first visualizations. - Get the code and reuse in your own projects. The ebook covers: - Intro to Data Science. - The Workflow of Data Science. - Data Science and Machine Learning. - Datasets to start right away. - Data Visualization Projects. (Python Code Understanding Recommended)
Data Science
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Author : Qurban A Memon
language : en
Publisher: CRC Press
Release Date : 2019-09-26
Data Science written by Qurban A Memon and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-26 with Computers categories.
The aim of this book is to provide an internationally respected collection of scientific research methods, technologies and applications in the area of data science. This book can prove useful to the researchers, professors, research students and practitioners as it reports novel research work on challenging topics in the area surrounding data science. In this book, some of the chapters are written in tutorial style concerning machine learning algorithms, data analysis, information design, infographics, relevant applications, etc. The book is structured as follows: • Part I: Data Science: Theory, Concepts, and Algorithms This part comprises five chapters on data Science theory, concepts, techniques and algorithms. • Part II: Data Design and Analysis This part comprises five chapters on data design and analysis. • Part III: Applications and New Trends in Data Science This part comprises four chapters on applications and new trends in data science.
Fundamentals Of Data Science
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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.
Data Science For Dummies
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Author : Lillian Pierson
language : en
Publisher: John Wiley & Sons
Release Date : 2015-03-09
Data Science For Dummies written by Lillian Pierson and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-03-09 with Business & Economics categories.
"Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles in organizations. Data Science For Dummies is the perfect starting point for IT professionals and students interested in making sense of their organization's massive data sets and applying their findings to real-world business scenarios. From uncovering rich data sources to managing large amounts of data within hardware and software limitations, ensuring consistency in reporting, merging various data sources, and beyond, you'll develop the know-how you need to effectively interpret data and tell a story that can be understood by anyone in your organization."--Provided by publisher.
Data Science For Beginners
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Author : Prof John Smith
language : en
Publisher: Independently Published
Release Date : 2018-12-12
Data Science For Beginners written by Prof John Smith and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-12 with categories.
DATA SCIENCE FOR BEGINNERS Introduction to Data Science: Python,Coding, Application, Statistics,Decision Tree, Neural Network, and Linear Algebra WHAT THIS BOOK WILL DO FOR YOU We will talk about what is the need for data science and then what exactly is data science some definitions and understand. The differences between data science and business intelligence,Then we will talk about the prerequisites for learning data science, and then what does the data scientist do. What are the activities performed by a data scientist as a part of his daily life and then we will talk about the data science lifecycle witha quick example and briefly touch upon the demand or ever-increasing demand for data scientist. Benefits of Data science Data Science: Automobile Data science: Aviation Data science can also be used to make promotional offers. Chapters Data science: Its Advantage Data science: Its Definition Process in data science Difference between business intelligence and data science Prerequisites for data science Machine learning. Data science: Tools and skills in data science. Data Science: Machine-learning algorithms Data science: Life cycle of a data science Data science: Exploratory data analysis Data science: Techniques for exploratory data analysis
Introduction To Data Science And Machine Learning
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Author : Keshav Sud
language : en
Publisher: BoD – Books on Demand
Release Date : 2020-03-25
Introduction To Data Science And Machine Learning written by Keshav Sud and has been published by BoD – Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-25 with Computers categories.
Introduction to Data Science and Machine Learning has been created with the goal to provide beginners seeking to learn about data science, data enthusiasts, and experienced data professionals with a deep understanding of data science application development using open-source programming from start to finish. This book is divided into four sections: the first section contains an introduction to the book, the second covers the field of data science, software development, and open-source based embedded hardware; the third section covers algorithms that are the decision engines for data science applications; and the final section brings together the concepts shared in the first three sections and provides several examples of data science applications.