Foundations Of Data Science With Python

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Foundations Of Data Science With Python

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Author : John M. Shea
language : en
Publisher: CRC Press
Release Date : 2024-02-22

Foundations Of Data Science With Python written by John M. Shea and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-22 with Business & Economics categories.

Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. This book is targeted toward engineers and scientists, but it should be readily understandable to anyone who knows basic calculus and the essentials of computer programming. It uses a computational-first approach to data science: the reader will learn how to use Python and the associated data-science libraries to visualize, transform, and model data, as well as how to conduct statistical tests using real data sets. Rather than relying on obscure formulas that only apply to very specific statistical tests, this book teaches readers how to perform statistical tests via resampling; this is a simple and general approach to conducting statistical tests using simulations that draw samples from the data being analyzed. The statistical techniques and tools are explained and demonstrated using a diverse collection of data sets to conduct statistical tests related to contemporary topics, from the effects of socioeconomic factors on the spread of the COVID-19 virus to the impact of state laws on firearms mortality. This book can be used as an undergraduate textbook for an Introduction to Data Science course or to provide a more contemporary approach in courses like Engineering Statistics. However, it is also intended to be accessible to practicing engineers and scientists who need to gain foundational knowledge of data science. Key Features: Applies a modern, computational approach to working with data Uses real data sets to conduct statistical tests that address a diverse set of contemporary issues Teaches the fundamentals of some of the most important tools in the Python data-science stack Provides a basic, but rigorous, introduction to Probability and its application to Statistics Offers an accompanying website that provides a unique set of online, interactive tools to help the reader learn the material

Foundations Of Data Science

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Author : Dr. Talluri Sunil Kumar, Dr. Radhika Pathi, Mr. Venu Aluri, K. Balasubramanian
language : en
Publisher: RK Publication
Release Date : 2025-05-02

Foundations Of Data Science written by Dr. Talluri Sunil Kumar, Dr. Radhika Pathi, Mr. Venu Aluri, K. Balasubramanian and has been published by RK Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Computers categories.

Foundations of Data Science offers a comprehensive introduction to data analysis, statistical modeling, machine learning, and computational techniques. Designed for students and professionals, it blends theory with practical applications, emphasizing critical thinking and data-driven decision-making across disciplines. The book equips readers to solve real-world problems using modern data science tools.

Foundations Of Data Science Principles And Applications

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Author : Dr. Punit Kumar Chaubey
language : en
Publisher: Academic Guru Publishing House
Release Date : 2024-07-24

Foundations Of Data Science Principles And Applications written by Dr. Punit Kumar Chaubey and has been published by Academic Guru Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-24 with Study Aids categories.

The thorough reference "Foundations of Data Science: Principles and Applications" explores the fundamental ideas and real-world uses of data science. The book is appropriate for both novices and those wishing to expand their knowledge of the subject since it is organised to lead readers from the fundamentals to more complex subjects. The book is broken up into many important parts. The first few chapters cover foundational ideas such data types, statistical procedures, and data visualisation strategies. Big data analytics, data mining methods, and machine learning algorithms are introduced throughout the book. A combination of practical examples and theoretical insights are used to convey each subject, making sure that readers not only understand the ideas but also learn how to apply them. The book encourages readers to think about the wider effect of their work by addressing the ethical and social aspects of data science in addition to its technical content. Readers will have a solid foundation in data science at the conclusion of the book, along with the know-how to take on challenging data problems and make significant contributions to the field.

Diy Data Science

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Author : Jonathan Dinu
language : en
Publisher: Addison-Wesley Professional
Release Date : 2017-05-23

Diy Data Science written by Jonathan Dinu and has been published by Addison-Wesley Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-05-23 with Computers categories.

Data science underlies Amazon's product recommender, LinkedIn's People You Know feature, Pandora's personalized radio stations, Stripe's fraud detectors, and the incredible insights arising from the world's increasingly ubiquitous sensors. In the future, the world's most interesting and impactful problems will be solved with data science. But right now, there's a shortage of data scientists in every industry, traditional schools can't teach students fast enough, and much of the knowledge data scientists need remains trapped in large tech companies. This comprehensive, practical tutorial is the solution. Drawing on his experience building Zipfian Academy's immersive 12-week data science training program, Jonathan Dinu brings together all you need to teach yourself data science, and successfully enter the profession. First, Dinu helps you internalize the data science "mindset": that virtually anything can be quantified, and once you have data, you can harvest amazing insights through statistical analysis and machine learning. He illuminates data science as it really is: a holistic, interdisciplinary process that encompasses the collection, processing, and communication of data: all that data scientists do, say, and believe. With this foundation in place, he teaches core data science skills through hands-on Python and SQL-based exercises integrated with a full book-length case study. Step by step, you'll learn how to leverage algorithmic thinking and the power of code, gain intuition about the power and limitations of current machine learning methods, and effectively apply them to real business problems. You'll walk through: Building basic and advanced models Performing exploratory data analysis Using data analysis to acquire and retain users or customers Making predictions with regression Using machine learning techniques Working with unsupervised learning and NLP Communicating with data Performing social network analyses Working with data at scale Getting started with Hadoop, Spark and other advanced tools Recognizing where common approaches break down, and how to overcome real world constraints Taking your next steps in your study and career Well-crafted appendices provide reference material on everything from the basics of Python and SQL to the essentials of probability, statistics, and linear algebra -- even preparing for your data science job interview!

Data Science For Undergraduates

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Author : National Academies of Sciences, Engineering, and Medicine
language : en
Publisher: National Academies Press
Release Date : 2018-10-11

Data Science For Undergraduates written by National Academies of Sciences, Engineering, and Medicine and has been published by National Academies Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-10-11 with Education categories.

Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field.

Foundations Of Data Science With Python

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Author : John M. Shea
language : en
Publisher: CRC Press
Release Date : 2024-02-20

Foundations Of Data Science With Python written by John M. Shea and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-20 with Business & Economics categories.

Foundations of Data Science with Python introduces readers to the fundamentals of data science, including data manipulation and visualization, probability, statistics, and dimensionality reduction. Intended for engineers and scientists, it can be used by any who know computer programming.

Foundations Of Statistics For Data Scientists

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Author : Alan Agresti
language : en
Publisher: CRC Press
Release Date : 2021-11-29

Foundations Of Statistics For Data Scientists written by Alan Agresti and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-29 with Business & Economics categories.

Foundations of Statistics for Data Scientists: With R and Python is designed as a textbook for a one- or two-term introduction to mathematical statistics for students training to become data scientists. It is an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modeling. The book assumes knowledge of basic calculus, so the presentation can focus on "why it works" as well as "how to do it." Compared to traditional "mathematical statistics" textbooks, however, the book has less emphasis on probability theory and more emphasis on using software to implement statistical methods and to conduct simulations to illustrate key concepts. All statistical analyses in the book use R software, with an appendix showing the same analyses with Python. Key Features: Shows the elements of statistical science that are important for students who plan to become data scientists. Includes Bayesian and regularized fitting of models (e.g., showing an example using the lasso), classification and clustering, and implementing methods with modern software (R and Python). Contains nearly 500 exercises. The book also introduces modern topics that do not normally appear in mathematical statistics texts but are highly relevant for data scientists, such as Bayesian inference, generalized linear models for non-normal responses (e.g., logistic regression and Poisson loglinear models), and regularized model fitting. The nearly 500 exercises are grouped into "Data Analysis and Applications" and "Methods and Concepts." Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website (http://stat4ds.rwth-aachen.de/) has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.

Fundamentals Of Data Analytics

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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.

Data Science And Big Data Foundations Tools And Techniques

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Author :
language : en
Publisher: Addition Publishing House
Release Date : 2024-12-02

Data Science And Big Data Foundations Tools And Techniques written by and has been published by Addition Publishing House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-02 with Antiques & Collectibles categories.

The world is increasingly driven by data, and as businesses and individuals generate more information than ever before, the demand for professionals skilled in data science and big data technologies continues to rise. Introduction to Data Science and Big Data aims to provide readers with a comprehensive understanding of these cutting-edge fields and the tools needed to navigate and make sense of vast amounts of data. This book covers the foundational concepts of data science and big data, including data collection, cleaning, and analysis. It dives into key data science methodologies, such as machine learning, statistical analysis, and predictive modeling. The book also explores big data technologies like Hadoop, Spark, and cloud computing, emphasizing how they can handle and process large datasets efficiently. Designed for students, professionals, and enthusiasts, this book presents complex topics in a clear and approachable manner. Each chapter is equipped with practical examples and real-world case studies to illustrate how data science and big data techniques are applied in various industries. By the end of this book, readers will have a solid understanding of how to leverage data for decision-making and problem-solving. As we stand on the precipice of a data-driven world, understanding how to manipulate and derive insights from vast amounts of data is no longer optional. With this book, readers will gain the skills necessary to thrive in the fast-evolving field of data science and big data, equipping them for success in the 21st century.

Data Science

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Author : Pallavi Vijay Chavan
language : en
Publisher: CRC Press
Release Date : 2022-08-15

Data Science written by Pallavi Vijay Chavan and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-15 with Business & Economics categories.

This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance, followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful.