Книги по Big Data/DataScience

As an aspiring data scientist, you appreciate why organizations rely on data for important decisions—whether it's for companies designing websites, cities deciding how to improve services, or scientists discovering how to stop the spread of disease. And you want the skills required to distill a messy pile of data into actionable insights. We call this the data science lifecycle: the process of col...

Business decisions in any context—operational, tactical, or strategic—can have considerable consequences. Whether the outcome is positive and rewarding or negative and damaging to the business, its employees, and stakeholders is unknown when action is approved. These decisions are usually made under the proverbial cloud of uncertainty.With this practical guide, data analysts, data scientists, and...

Introduces students to appropriate use of computer programming within the scientific disciplines using Python. Discusses several common applications of programming and implementation using real world examples and hands on programming exercises. Students learn how to model situations such as image recognition, medical diagnosis, spread of disease, and others.The text could be used by students and l...

Перед вами незаменимое руководство для тех, кто хочет быстро и эффективно освоить Python и использовать его в научной деятельности. Книга не только объясняет основы, но и демонстрирует применение языка для анализа данных, визуализации, моделирования и решения сложных исследовательских задач.Издание идеально подходит студентам, преподавателям, ученым, а также программистам — как начинающим, так и о...

Are you an experienced statistician or data professional looking for a powerful, efficient, and versatile programming language to turbocharge your data analysis and machine learning projects? Look no further! "Statistics with Rust" is your comprehensive resource to unlock Rust's true potential in modern statistical methods.This book is tailored specifically for statisticians and data professionals...

The book is designed to serve as a textbook for courses offered to undergraduate and graduate students enrolled in data science. This book aims to help the readers understand the basic and advanced concepts for developing simple programs and the fundamentals required for building machine learning models. The book covers basic concepts like data types, operators, and statements that enable the read...

An Introduction to R and Python for Data Analysis helps teach students to code in both R and Python simultaneously. As both R and Python can be used in similar manners, it is useful and efficient to learn both at the same time, helping lecturers and students to teach and learn more, save time, whilst reinforcing the shared concepts and differences of the systems. This tandem learning is highly use...

Julia as a Second Language introduces Julia to readers with a beginning-level knowledge of another language like Python or JavaScript. You’ll learn by coding engaging hands-on projects that encourage you to apply what you’re learning immediately. Don’t be put off by Julia’s reputation as a scientific programming language—there’s no data science or numerical computing knowledge required. You can ge...

This comprehensive guide is designed to teach you the skills you need to become a top-paying data analyst. With a focus on the powerful Python programming language, you'll learn how to collect, clean, and analyze data like a pro. But that's not all - you'll also discover how to use this data to make informed business decisions and drive real results.KEY FEATURES:How to use Python's built-in librar...

Modern systems contain multi-core CPUs and GPUs that have the potential for parallel computing. But many scientific Python tools were not designed to leverage this parallelism. With this short but thorough resource, data scientists and Python programmers will learn how the Dask open source library for parallel computing provides APIs that make it easy to parallelize PyData libraries including NumP...

Are you looking to level up your data visualization skills in Python? Look no further! Introducing the ultimate guide to 101 visualizations using just one dataset. Whether you're a beginner or an experienced data scientist, this comprehensive guide will take you on a visual journey through various plotting techniques, insights, and patterns that can be explored with Python and a single dataset. In...

Data fabric, data lakehouse, and data mesh have recently appeared as viable alternatives to the modern data warehouse. These new architectures have solid benefits, but they're also surrounded by a lot of hyperbole and confusion. This practical book provides a guided tour of these architectures to help data professionals understand the pros and cons of each.James Serra, big data and data warehousin...

Rather than presenting Python as Java or C, this textbook focuses on the essential Python programming skills for data scientists and advanced methods for big data analysts.Unlike conventional textbooks, it is based on Markdown and uses full-color printing and a code-centric approach to highlight the 3C principles in data science: creative design of data solutions, curiosity about the data lifecycl...

A hands-on, easy-to-comprehend guide that is perfect for anyone who needs to understand algorithms.With the explosive growth in the amount of data and the diversity of computing applications, efficient algorithms are needed now more than ever. Programming languages come and go, but the core of programming-algorithms and data structures-remains the same.Absolute Beginner's Guide to Algorithmsis the...

Среди организаций, работающих с крупными объемами данных на регулярной основе, реляционная система управления базами данных MySQL стала популярным решением по обработке структурированных больших данных. В книге вы познакомитесь с тем, как администраторы баз данных могут использовать MySQL для обработки миллиардов записей и извлечения данных с производительностью, сравнимой или превосходящей коммер...