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Feature Engineering for Machine Learning Principles and Techniques for Data Scientists - Alice Zheng, Amanda Casari 2018 PDF O;kav_1Reilly Media BOOKS PROGRAMMING
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Feature Engineering for Machine Learning Principles and Techniques for Data Scientists
Author: Alice Zheng, Amanda Casari
Year: 2018
Pages: 216
Format: PDF
File size: 15 MB
Language: ENG



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Book Description: Feature Engineering for Machine Learning: Principles and Techniques for Data Scientists Author: Alice Zheng, Amanda Casari O'Reilly Media 2018 216 Format: Paperback/eBook Genre: Computer Science, Artificial Intelligence, Machine Learning Summary: Feature engineering is an essential step in the machine learning pipeline that is often overlooked. This book delves into the process of transforming raw data into formats suitable for machine learning models. It covers various techniques for representing text, image, and other types of data, demonstrating their applications in real-world scenarios. With each chapter focusing on a different data problem, readers will gain a comprehensive understanding of feature engineering principles and their practical applications. Long Description: In the ever-evolving world of technology, it is crucial to understand the process of developing modern knowledge and its impact on humanity. Feature engineering plays a vital role in the machine learning pipeline, yet it is rarely explored as a standalone topic. This book fills this knowledge gap by providing a detailed examination of feature engineering techniques and their applications. The book begins with an introduction to feature engineering, highlighting its importance in the machine learning process. The author then delves into the various techniques used to represent text, image, and other types of data.
Feature Engineering for Machine arning: Principles and Techniques for Data Scientists Автор: Alice Zheng, Amanda Casari O'Reilly Media 2018 216 Формат: Paperback/eBook Жанр: информатика, искусственный интеллект, резюме по машинному обучению: Feature engineering - важный шаг в конвейере машинного обучения, который часто упускают из виду Эта книга углубляется в процесс преобразования необработанных данных в форматы, подходящие для моделей машинного обучения. Он охватывает различные методы представления текста, изображений и других типов данных, демонстрируя их применение в реальных сценариях. С каждой главой, посвященной различным проблемам с данными, читатели получат полное понимание принципов проектирования функций и их практического применения. Длинное описание: В постоянно развивающемся мире технологий крайне важно понимать процесс развития современных знаний и их влияние на человечество. Разработка функций играет жизненно важную роль в конвейере машинного обучения, однако она редко рассматривается как отдельная тема. Эта книга заполняет этот пробел в знаниях, предоставляя подробный анализ методов проектирования функций и их приложений. Книга начинается с введения в feature engineering, подчёркивающего её важность в процессе машинного обучения. Затем автор углубляется в различные методы, используемые для представления текста, изображения и других типов данных.
Feature Engineering for Machine arning: Principles and Techniques for Data Scientists Автор: Alice Zheng, Amanda Casari O'Reilly Media 2018 216 Formato: Paperback/eBook Género: informática, inteligencia artificial, currículum on machine learning: Feature engineering es un paso importante en la línea de montaje del aprendizaje automático que a menudo se pasa por alto Este libro profundiza en el proceso de convertir datos en bruto en formatos adecuados para los modelos de aprendizaje automático. Abarca diferentes métodos para representar texto, imágenes y otros tipos de datos, demostrando su aplicación en escenarios reales. Con cada capítulo dedicado a los diferentes problemas de datos, los lectores tendrán una comprensión completa de los principios de diseño de funciones y sus aplicaciones prácticas. Descripción larga: En un mundo de tecnología en constante evolución, es fundamental comprender el proceso de desarrollo del conocimiento moderno y su impacto en la humanidad. desarrollo de funciones juega un papel vital en la línea de montaje del aprendizaje automático, sin embargo, rara vez se considera como un tema separado. Este libro llena este vacío de conocimiento al proporcionar un análisis detallado de los métodos de diseño de funciones y sus aplicaciones. libro comienza con una introducción a la ingeniería de características, enfatizando su importancia en el proceso de aprendizaje automático. A continuación, el autor profundiza en los diferentes métodos utilizados para representar texto, imagen y otros tipos de datos.
Feature Engineering for Machine arning: Principles and Techniques for Data Scientists Автор: Alice Zheng, Amanda Casari O'Reilly Media 2018 216 Formato: Paperback/eBook Genere: informatica, intelligenza artificiale, curriculum sull'apprendimento automatico: feature engineering è un passo importante nella catena di montaggio dell'apprendimento automatico, che spesso viene trascurato. Questo libro viene approfondito nel processo di conversione dei dati non trattati in formati adatti ai modelli di apprendimento automatico. Include diversi metodi per la rappresentazione di testo, immagini e altri tipi di dati, dimostrandone l'uso in scenari reali. Con ogni capitolo dedicato alle diverse problematiche dei dati, i lettori avranno una conoscenza completa dei principi della progettazione e della loro applicazione pratica. Lunga descrizione: In un mondo in continua evoluzione della tecnologia, è fondamentale comprendere il processo di sviluppo delle conoscenze moderne e il loro impatto sull'umanità. Lo sviluppo delle funzioni svolge un ruolo fondamentale nella catena di montaggio dell'apprendimento automatico, ma raramente viene considerato come un tema separato. Questo libro colma questo spazio di conoscenza fornendo un'analisi dettagliata dei metodi di progettazione delle funzioni e delle relative applicazioni. Il libro inizia con l'introduzione di una feature engineering che ne sottolinea l'importanza nel processo di apprendimento automatico. Quindi l'autore approfondisce i vari metodi utilizzati per rappresentare il testo, l'immagine e altri tipi di dati.
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機械学習のための機能エンジニアリング:データサイエンティストのための原則とテクニック: Alice Zheng、 Amanda Casari O'Reilly Media 2018 216フォーマット:ペーパーバック/電子ブックジャンル: コンピュータサイエンス、人工知能、機械学習の概要:特徴工学は、しばしば見落とされる機械学習パイプラインの重要なステップこの本は、機械学習モデルに適したフォーマットに生のデータを変換するプロセスを掘り下げます。テキスト、画像、その他の種類のデータを表すさまざまな方法をカバーし、実際のシナリオでそのアプリケーションを実証しています。さまざまなデータ問題に専念する各章で、読者は機能設計の原則とその実用的なアプリケーションを完全に理解することになります。長い説明:絶えず発展している技術の世界では、現代の知識の発展と人類への影響を理解することが非常に重要です。機能開発は機械学習パイプラインで重要な役割を果たしますが、別のトピックとして扱われることはめったにありません。この本は、機能設計技術とその応用の詳細な分析を提供することによって、この知識のギャップを埋めます。本書は、機械学習の過程におけるその重要性を強調し、特徴工学の紹介から始まります。著者は、テキスト、画像、およびその他の種類のデータを表現するために使用されるさまざまな技術を掘り下げます。

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