Название: Effective Data Science Infrastructure: How to Make Data Scientists Productive
Автор: Ville Tuulos
Издательство: Manning Publications
Год: 2022
Формат: True PDF
Страниц: 353
Размер: 17,8 Mb
Язык: English

Effective Data Science Infrastructure is a hands-on guide to assembling infrastructure for data science and machine learning applications. It reveals the processes used at Netflix and other data driven companies to manage their cutting edge data infrastructure. As you work through this easy-to-follow guide, you’ll set up end-to end infrastructure from the ground up, with a fully customizable process you can easily adapt to your company. You’ll learn how you can make data scientists more productive with your existing cloud infrastructure, a stack of open source software, and idiomatic Python. Throughout, you’ll follow a human-centric approach focused on user experience and meeting the unique needs of data scientists.

Название: Как проектировать программы
Автор: Фелляйзен Маттиас, Флэтт Мэтью, Финдлер Роберт Брюс
Издательство: ДMK
Год: 2022
Формат: True PDF
Страниц: 726
Размер: 10,5 Mb
Язык: Русский

Цель этой книги – познакомить читателей с системным подходом к проектированию и сформировать у них правильные навыки программирования, которые предполагают пошаговое планирование и понимание рабочих задач на каждом этапе создания программы. В фокусе книги – общие принципы проектирования программ, поэтому используется не стандартный промышленный язык, а специализированный язык обучения Racket, а также среда программирования DrRacket, которая обеспечивает увлекательное обучение. Возможности среды растут по мере того, как читатель осваивает материал, – вплоть до поддержки полноценного языка, пригодного для решения всего спектра задач программирования.

Название: Random Matrix Methods for Machine Learning
Автор: Romain Couillet, Zhenyu Liao,
Издательство: Cambridge University Press
Год: 2022
Страниц: 411
Размер: 10,62 МБ
Формат: PDF
Язык: English

This book presents a unified theory of random matrices for applications in machine learning, offering a large-dimensional data vision that exploits concentration and universality phenomena. This enables a precise understanding, and possible improvements, of the core mechanisms at play in real-world machine learning algorithms.

Название: Practical Machine Learning with Spark
Автор: Gourav Gupta, Dr. Manish Gupta, Dr. Inder Singh Gupta
Издательство: BPB Publications
Год: 2022
Формат: PDF
Страниц: 554
Размер: 18 Mb
Язык: English

This book provides the reader with an up-to-date explanation of Machine Learning and an in-depth, comprehensive, and straightforward understanding of the architectural techniques used to evaluate and anticipate the futuristic insights of data using Apache Spark.

Название: Network Programming in Python
Автор: John Galbraith
Издательство: BPB Publications
Год: 2022
Формат: PDF
Страниц: 544
Размер: 10 Mb
Язык: English

This book includes revisions for Python 3 as well as all of the classic topics covered, such as network protocols, network data and errors, email, server architecture, and HTTP and web applications.

Название: Productive and Efficient Data Science with Python
Автор: Dr. Tirthajyoti Sarkar
Издательство: Apress
Год: 2022
Формат: True PDF
Страниц: 395
Размер: 18,8 Mb
Язык: English

This book focuses on the Python-based tools and techniques to help you become highly productive at all aspects of typical data science stacks such as statistical analysis, visualization, model selection, and feature engineering.
You’ll review the inefficiencies and bottlenecks lurking in the daily business process and solve them with practical solutions. Automation of repetitive data science tasks is a key mindset that is promoted throughout the book. You’ll learn how to extend the existing coding practice to handle larger datasets with high efficiency with the help of advanced libraries and packages that already exist in the Python ecosystem.

Название: Beginning Data Science in R 4: Data Analysis, Visualization, and Modelling for the Data Scientist 2nd Edition
Автор: Thomas Mailund
Издательство: Apress
Год: 2022
Формат: True PDF
Страниц: 528
Размер: 11 Mb
Язык: English

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R.

Название: DevOps in Python: Infrastructure as Python, 2nd Edition
Автор: Moshe Zadka
Издательство: Apress
Год: 2022
Формат: True PDF, ePUB
Страниц: 245
Размер: 10 Mb
Язык: English

Take advantage of Python to automate complex systems with readable code. This new edition will help you move from operations/system administration into easy-to-learn coding.
You'll start by writing command-line scripts and automating simple DevOps-style tasks followed by creating reliable and fast unit tests designed to avoid incidents caused by buggy automation. You’ll then move on to more advanced cases, like using Jupyter as an auditable remote-control panel and writing Ansible and Salt extensions.

Название: Network Programming with Go Language 2nd Edition
Автор: Dr. Jan Newmarch, Ronald Petty
Издательство: Apress
Год: 2022
Формат: True PDF, ePUB
Страниц: 386
Размер: 10 Mb
Язык: English

Dive into key topics in network architecture implemented with the Google-backed open source Go programming language. Networking topics such as data serialization, application level protocols, character sets and encodings are discussed and demonstrated in Go. This book has been updated to the Go version 1.18 which includes modules, generics, and fuzzing along with updated and additional examples.

Название: Regression Analysis in R A Comprehensive View for the Social Sciences
Автор: Jocelyn H. Bolin
Издательство: CRC Press
Год: 2022
Формат: True PDF
Страниц: 193
Размер: 10 Mb
Язык: English

Regression Analysis in R: A Comprehensive View for the Social Sciences covers the basic applications of multiple linear regression all the way through to more complex regression applications and extensions. Written for graduate level students of social science disciplines this book walks readers through bivariate correlation giving them a solid framework from which to expand into more complicated regression models. Concepts are demonstrated using R software and real data examples.