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Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and Scikit-Learn - Abdelaziz Testas 2023 PDF | EPUB | MOBI Apress BOOKS PROGRAMMING
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Distributed Machine Learning with PySpark Migrating Effortlessly from Pandas and Scikit-Learn
Author: Abdelaziz Testas
Year: 2023
Pages: 500
Format: PDF | EPUB | MOBI
File size: 10.1 MB
Language: ENG



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Book Description: Distributed Machine Learning with PySpark - Migrating Effortlessly from Pandas and Scikit-Learn Abdelaziz Testas Publisher: Apress 2023 500 Format: Paperback/eBook Genre: Technology, Machine Learning, Artificial Intelligence, Python Programming Synopsis: In an era of vast amounts of data, the need for efficient and scalable machine learning techniques has become increasingly important. As a result, data scientists and machine learning practitioners must adapt to new technologies that can handle large datasets and perform complex computations quickly. Distributed Machine Learning with PySpark is a comprehensive guide to migrating from Pandas and Scikit-learn to PySpark, enabling faster data processing times and more accurate modeling. This book provides a roadmap for data scientists looking to transition from small data libraries to big data processing and machine learning with PySpark. Introduction: The world of machine learning has evolved significantly over the past decade, with the emergence of distributed computing and big data revolutionizing the field.
Distributed Machine arning with PySpark - Migrating Effortly from Pandas and Scikit-arn Абдельазиз Тестас Издатель: Apress 2023 500 Формат: Paperback/eBook Жанр: технологии, машинное обучение, искусственный интеллект, синопсис программирования на Python: в эпоху огромного количества данных, потребность в эффективных и масштабируемых методах машинного обучения становится все более важной. В результате специалисты по обработке данных и практики машинного обучения должны адаптироваться к новым технологиям, которые могут обрабатывать большие наборы данных и быстро выполнять сложные вычисления. Распределенное машинное обучение с помощью PySpark - это комплексное руководство по переходу с Pandas и Scikit-learn на PySpark, позволяющее ускорить обработку данных и повысить точность моделирования. В этой книге представлена дорожная карта для специалистов по анализу данных, которые хотят перейти от небольших библиотек данных к обработке больших данных и машинному обучению с помощью PySpark. Введение: Мир машинного обучения значительно изменился за последнее десятилетие, с появлением распределенных вычислений и больших данных, революционизирующих эту область.
Distribuido Machine arning with PySpark - Migrando Effortly from Pandas and Scikit-arn Abdelaziz Testas Editor: Apress 2023 500 Formato: Paperback/eBook Género: tecnología, aprendizaje automático, inteligencia artificial, sinopsis de programación en Python: en una era de enormes cantidades de datos, la necesidad de métodos de aprendizaje automático eficientes y escalables es cada vez más importante. Como resultado, los profesionales del procesamiento de datos y las prácticas de aprendizaje automático deben adaptarse a las nuevas tecnologías que pueden procesar grandes conjuntos de datos y realizar computación compleja rápidamente. aprendizaje automático distribuido con PySpark es una guía completa para la transición de Pandas y Scikit-learn a PySpark que le permite acelerar el procesamiento de datos y mejorar la precisión de la simulación. Este libro presenta una hoja de ruta para los especialistas en análisis de datos que desean pasar de pequeñas bibliotecas de datos a procesamiento de big data y aprendizaje automático con PySpark. Introducción: mundo del aprendizaje automático ha cambiado significativamente en la última década, con la aparición de la computación distribuida y el big data revolucionando este campo.
O livro «Golyawkin WV Reunião de 10 Livros para Crianças», de Viktor Vladimir Golyawkin, é uma coleção de dez histórias escritas para crianças, cada uma mostrando uma mistura única de espírito, humor e curta. As histórias têm uma concisão que as torna acessíveis e fascinantes para os jovens leitores. O uso do humor e da leveza por parte do autor é raro na literatura infantil, onde a maioria das histórias geralmente são mais longas e mais longas. No entanto, a abordagem de Golyavkin em relação à narrativa foi eficaz para chamar a atenção dos jovens leitores e para manter o seu envolvimento. Os personagens das histórias de Golyawkin são sempre vivos e encantadores, com um conjunto de personagens engraçados e bonitos em cada conto. As histórias são tão curtas que podem ser lidas em um sentado, o que as torna perfeitas para dormir ou em qualquer outro momento, quando preferencialmente uma leitura rápida e interessante. Alguns contos notáveis incluem «Drawing Four Colors» e «ck», que mostram a capacidade do autor de transmitir lições significativas através de anedotas humorísticas. Um dos temas-chave presentes ao longo do livro é a importância da compreensão e adaptação ao progresso técnico. Em «Drawing Four Colors», o protagonista aprende a desenhar usando apenas quatro cores, ilustrando o valor da simplicidade e eficiência em atividades criativas. Do mesmo modo, o Relatório dos Doentes aborda os problemas relacionados com a orientação em um mundo em rápida mudança e enfatiza a necessidade de flexibilidade e sustentabilidade face ao progresso tecnológico.
Distributed Machine arning with - Migrating Effortly from Pandas and Scikit-arn Abdelaziz Testas Editore: Apress 20200 Formato: Tecnologia, apprendimento automatico, intelligenza artificiale, sinopsi di programmazione su Python: in un'epoca di enorme quantità di dati, il bisogno di metodi di apprendimento automatico efficienti e scalabili diventa sempre più importante. Di conseguenza, gli esperti di elaborazione dei dati e di apprendimento automatico devono adattarsi alle nuove tecnologie in grado di elaborare set di dati di grandi dimensioni e eseguire elaborazioni complesse in tempi rapidi. L'apprendimento automatico distribuito con l'PySpark è una guida completa per la transizione da Pandas e Scikit-learn a PySpark, che consente di accelerare l'elaborazione dei dati e migliorare l'accuratezza delle simulazioni. Questo libro fornisce una road map per gli esperti di analisi dei dati che desiderano passare dalle piccole librerie di dati all'elaborazione dei big data e all'apprendimento automatico con l'PySpark. Introduzione: Il mondo dell'apprendimento automatico è cambiato notevolmente nell'ultimo decennio, con l'avvento dei calcoli distribuiti e dei big data che rivoluzionano questo campo.
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Distributed Machine arning with PySpark-パンダとScikit-arn Abdelaziz Testasパブリッシャー:Apress 2023 500フォーマット:ペーパーバック/eBookジャンル:テクノロジー、機械学習、人工知能、プログラミングSynopson Python:膨大なデータの時代において、効率的でスケーラブルな機械学習手法の必要性はますます重要になってきています。その結果、データサイエンティストや機械学習プラクティショナーは、大規模なデータセットを処理し、複雑な計算を迅速に実行できる新しい技術に適応する必要があります。PySparkによる分散機械学習は、PandasとScikit-learnからPySparkへの移行に関する包括的なガイドであり、データ処理の高速化とシミュレーション精度の向上を可能にします。この本は、小さなデータライブラリからビッグデータ処理、PySparkによる機械学習に移行しようとするデータサイエンティストのためのロードマップを提供します。はじめに:機械学習の世界は、分散コンピューティングとビッグデータの出現により、この10間で大きく変化しました。

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