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 Название: Ultimate Enterprise Data Analysis and Forecasting using Python: Leverage Cloud platforms with Azure Time Series Insights and AWS Forecast Components for Time Series Analysis and Forecasting with Deep learning Modeling using Python
Автор: Shanthababu Pandian
Издательство: Orange Education Pvt Ltd, AVA
Год: December 2023
Страниц: 503
Язык: английский
Формат: epub (true)
Размер: 18.3 MB
Practical Approaches to Time Series Analysis and Forecasting using Python for Informed Decision-Making. This book covers various aspects of Time Series Analysis and Forecasting using the Python language, emphasizing the importance of time series analysis from an industry perspective for in-depth analysis and forecasting, with real-time use cases and required examples. The primary objective of this book is to provide a detailed pack of time series analysis and forecasting methods, essential in the current digital market, and grow business opportunities using various techniques from an AIML perspective. This book aims to connect the Time Series and Forecasting problem statements across multiple industries and demonstrate how to provide solutions using currently available tools, technology, and evidence of success stories. This book promises that by the end of the reading, the readers will understand time series and forecasting techniques, and also learn how to analyze, design, and maintain the solutions. In this manner, readers can follow the correct path to take the time series components, work on them with Python packages, and understand the data for analysis and productive solutions, such as predicting or forecasting. This book covers the expectations of Data Analysts, Data Scientists, and Machine Learning Engineers who will be involved in time series analysis and forecasting-related projects. This book helps those interested in time series analysis. The book begins with an introduction to Python and its essential packages. It then delves into various aspects of time series data analysis and models from both traditional and ML methods, followed by their implementation in the cloud environment. | |
Разместил: Ingvar16 4-01-2024, 10:34 | Комментарии: 0 | Подробнее
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 Название: Deep Learning for Engineers
Автор: Tariq M. Arif, Md Adilur Rahim
Издательство: CRC Press
Год: 2024
Страниц: 170
Язык: английский
Формат: pdf (true)
Размер: 18.9 MB
Deep Learning for Engineers introduces the fundamental principles of Deep Learning along with an explanation of the basic elements required for understanding and applying Deep Learning models. As a comprehensive guideline for applying Deep Learning models in practical settings, this book features an easy-to-understand coding structure using Python and PyTorch with an in-depth explanation of four typical deep learning case studies on image classification, object detection, semantic segmentation, and image captioning. The fundamentals of convolutional neural network (CNN) and recurrent neural network (RNN) architectures and their practical implementations in science and engineering are also discussed. Some basic knowledge of Python programming is required to follow this book. However, no chapter is devoted to teaching Python programming. Instead, we demonstrated relevant Python commands followed by brief descriptions throughout this book. A common roadblock to exploring the deep learning field by engineering students, researchers, or non-data science professionals is the variation of probabilistic theories and the notations used in Data Science or Computer Science books. In order to avoid this complexity, in this book, we mainly focus on the practical implementation part of deep learning theory using Python programming. This book includes exercise problems for all case studies focusing on various fine-tuning approaches in Deep Learning. Science and engineering students at both undergraduate and graduate levels, academic researchers, and industry professionals will find the contents useful. | |
Разместил: Ingvar16 4-01-2024, 09:45 | Комментарии: 0 | Подробнее
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 Название: Data Science and Machine Learning for Non-Programmers: Using SAS Enterprise Miner
Автор: Dothang Truong
Издательство: CRC Press
Год: 2024
Страниц: 590
Язык: английский
Формат: pdf (true)
Размер: 35.9 MB
As data continues to grow exponentially, knowledge of Data Science and Machine Learning has become more crucial than ever. Machine Learning has grown exponentially; however, the abundance of resources can be overwhelming, making it challenging for new learners. This book aims to address this disparity and cater to learners from various non-technical fields, enabling them to utilize Machine Learning effectively. Adopting a hands-on approach, readers are guided through practical implementations using real datasets and SAS Enterprise Miner, a user-friendly data mining software that requires no programming. Throughout the chapters, two large datasets are used consistently, allowing readers to practice all stages of the data mining process within a cohesive project framework. This book also provides specific guidelines and examples on presenting data mining results and reports, enhancing effective communication with stakeholders. The book begins with Part I, introducing the core concepts of data science, data mining, and Machine Learning. My aim is to present these principles without overwhelming readers with complex math, empowering them to comprehend the underlying mechanisms of various algorithms and models. This foundational knowledge will enable readers to make informed choices when selecting the right tool for specific problems. In Part II, I focus on the most popular Machine Learning algorithms, including regression methods, decision trees, neural networks, ensemble modeling, principal component analysis, and cluster analysis. | |
Разместил: Ingvar16 3-01-2024, 19:09 | Комментарии: 0 | Подробнее
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 Название: Geographic Data Science with Python
Автор: Sergio Rey, Dani Arribas-Bel, Levi John Wolf
Издательство: CRC Press
Год: 2023
Страниц: 411
Язык: английский
Формат: pdf (true)
Размер: 27.5 MB
This book provides the tools, the methods, and the theory to meet the challenges of contemporary Data Science applied to geographic problems and data. In the new world of pervasive, large, frequent, and rapid data, there are new opportunities to understand and analyze the role of geography in everyday life. Geographic Data Science with Python introduces a new way of thinking about analysis, by using geographical and computational reasoning, it shows the reader how to unlock new insights hidden within data. It presents concepts in a far more geographic way than competing textbooks, covering spatial data, mapping, and spatial statistics whilst covering concepts, such as clusters and outliers, as geographic concepts. Intended for data scientists, GIScientists, and geographers, the material provided in this book is of interest due to the manner in which it presents geospatial data, methods, tools, and practices in this new field. | |
Разместил: Ingvar16 3-01-2024, 18:32 | Комментарии: 0 | Подробнее
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 Название: Python. К вершинам мастерства
Автор: Лучано Рамальо
Издательство: ДМК-Пресс
Страниц: 769
Формат: pdf/djvu
Размер: 20 мб
Год издания: 2016
Язык Python настолько прост, что научиться продуктивно писать на нем программы можно быстро, но зачастую вы при этом используете не все имеющиеся в нем возможности.
Это практическое пособие покажет, как создавать эффективный идиоматичный код на Python, задействуя его лучшие — и иногда несправедливо игнорируемые — черты. Автор, Лучано Рамальо, рассказывает от базовых средствах и библиотеках Python и демонстрирует, как сделать код одновременно короче, быстрее и понятнее. Многие опытные программисты стараются подогнать Python под приемы, знакомые им по работе с другими языками. Эта книга покажет им, как достичь истинного профессионализма в программировании на Python 3. | |
Разместил: rivasss 3-01-2024, 09:48 | Комментарии: 1 | Подробнее
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 Название: Image Processing and Machine Learning, Volume 1: Foundations of Image Processing
Автор: Erik Cuevas, Alma Nayeli Rodr?guez
Издательство: CRC Press
Год: 2024
Страниц: 225
Язык: английский
Формат: pdf (true)
Размер: 40.9 MB
Image processing and Machine Learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, Machine Learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this first installment explores the fundamental concepts and techniques in image processing, starting with pixel operations and their properties and exploring spatial filtering, edge detection, image segmentation, corner detection, and geometric transformations. Our primary objective was to create a comprehensive textbook that serves as an invaluable resource for an image processing class. With this goal in mind, we carefully crafted a book that encompasses both the theoretical foundations and practical applications of the most prevalent image processing methods. From pixel operations to geometric transformations, spatial filtering to image segmentation, and edge detection to color image processing, we have meticulously covered a wide range of topics essential to understanding and working with images. Moreover, recognizing the increasing relevance of ML in image processing, we have incorporated fundamental ML concepts and their applications in this field. By introducing readers to these concepts, we aim to equip them with the necessary knowledge to leverage ML techniques for various image processing tasks. Volume 1 is organized in a way that allows readers to easily understand the goal of each chapter and reinforce their understanding through practical exercises using MATLAB programs. | |
Разместил: Ingvar16 3-01-2024, 09:44 | Комментарии: 0 | Подробнее
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 Название: Image Processing and Machine Learning, Volume 2: Advanced Topics in Image Analysis and Machine Learning
Автор: Erik Cuevas, Alma Nayeli Rodriguez
Издательство: CRC Press
Год: 2024
Страниц: 239
Язык: английский
Формат: pdf (true)
Размер: 31.6 MB
Image processing and Machine Learning are used in conjunction to analyze and understand images. Where image processing is used to pre-process images using techniques such as filtering, segmentation, and feature extraction, Machine Learning algorithms are used to interpret the processed data through classification, clustering, and object detection. This book serves as a textbook for students and instructors of image processing, covering the theoretical foundations and practical applications of some of the most prevalent image processing methods and approaches. Divided into two volumes, this second installment explores the more advanced concepts and techniques in image processing, including morphological filters, color image processing, image matching, feature-based segmentation utilizing the mean shift algorithm, and the application of singular value decomposition for image compression. This second volume also incorporates several important Machine Learning techniques applied to image processing, building on the foundational knowledge introduced in Volume 1. Machine Learning (ML) is a branch of artificial intelligence (AI) that enables systems to learn from data and make informed predictions or decisions without the need for explicit programming. ML finds extensive applications in various domains. For instance, in automation, ML algorithms can automate tasks that would otherwise rely on human intervention, thereby reducing errors and enhancing overall efficiency. Predictive analytics is another area where ML plays a crucial role. By analyzing vast datasets, ML models can detect patterns and make predictions, facilitating applications such as stock market analysis, fraud detection, and customer behavior analysis. We have observed that students grasp the material more effectively when they have access to code that they can manipulate and experiment with. In line with this, our book utilizes MATLAB as the programming language for implementing the systems. | |
Разместил: Ingvar16 3-01-2024, 09:03 | Комментарии: 0 | Подробнее
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Название: Unity. Полное руководство
Автор: Корнилов А.В.
Издательство: СПб.: Наука и техника
Год: 2021
Формат: pdf
Страниц: 496
Размер: 79 mb
Язык: Русский
В этой книге мы расскажем, как с использованием Unity (популярной межплатформенной среды разработки компьютерных игр) вы сможете САМИ создавать свои игры и трехмерные миры, причем без лишних затрат и профессиональных навыков программирования.
Книга поделена на три части. Первая часть посвящена изучению интерфейса и основных возможностей Unity. Мы поговорим о двух- и трехмерных проектах; рассмотрим ключевые особенности Unity; узнаем, как использовать ассеты; подробном изучим интерфейс Unity; узнаем об игровых объектах, сценах, камерах, источниках света; создадим свои первые Unitу-проекты. | |
Разместил: na5ballov 3-01-2024, 08:11 | Комментарии: 0 | Подробнее
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 Название: Расширенная аналитика с PySpark: Практические примеры анализа больших наборов данных с использованием Python и Spark
Автор: Акаш Тандон, Сэнди Райза, Ури Ласерсон
Издательство: БХВ-Петербург
Год: 2023
Страниц: 226
Язык: русский
Формат: pdf, djvu
Размер: 36.3 MB
Книга посвящена практическим методам анализа больших объемов данных с использованием языка Python и фреймворка Spark, она знакомит с моделью программирования Spark и основами системы с открытым исходным кодом PySpark. Каждая глава описывает отдельный аспект анализа данных, показаны основы обработки данных в PySpark и Python на примере очистки данных, подробно освещается машинное обучение с помощью Spark. Книга поможет читателю понять, как устроен и работает весь конвейер PySpark для комплексной аналитики больших наборов данных: от создания и оценки моделей до очистки, предварительной обработки и исследования данных с особым акцентом на производственные приложения. Отдельные главы посвящены обработке изображений и библиотеке Spark NLP. Эта книга не рассказывает о достоинствах и недостатках PySpark. Книга знакомит с моделью программирования Spark и основами PySpark — API Python для Spark. Тем не менее она не претендует на то, чтобы служить справочником по Spark или быть исчерпывающим путеводителем по всем закоулкам Spark. Она также не претендует на роль справочника по машинному обучению, статистике или линейной алгебре, хотя во многих главах содержится небольшой вводный материал перед их использованием. Эта книга поможет читателю понять, как устроен и работает весь конвейер PySpark для комплексной аналитики больших наборов данных, а это не только создание и оценка моделей, но также очистка, предварительная обработка и исследование данных с особым акцентом на производственные приложения. | |
Разместил: Ingvar16 3-01-2024, 07:31 | Комментарии: 0 | Подробнее
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Название: Библиотека программирования на Python. Сборник (180 книг)
Автор(ы): разные
Издательство: Москва
Год: 2001-2024
Страниц: 1000+
Формат: pdf
Размер: 4 Гб
Язык: русский
Сборник книг "Библиотека программирования на Python" предназначен как для опытных мастеров своего дела, так и для тех, кто только приступил к изучению программирования. В данном выпуске библиотеки книги, посвященные изучению Python.
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Разместил: MIHAIL62 3-01-2024, 00:23 | Комментарии: 2 | Подробнее
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