| 書目名稱 | Machine Learning with PySpark | | 副標題 | With Natural Languag | | 編輯 | Pramod Singh | | 視頻video | http://file.papertrans.cn/621/620715/620715.mp4 | | 概述 | Covers how to transition from Python-based ML models to PySpark-based large scale models.Covers how to automate your data workflow using Airflow.Explains the end-to end machine learning pipeline for m | | 圖書封面 |  | | 描述 | .Master the new features in PySpark 3.1 to develop data-driven, intelligent applications. This updated edition covers topics ranging from building scalable machine learning models, to natural language processing, to recommender systems...Machine Learning with PySpark, Second Edition. begins with the fundamentals of Apache Spark, including the latest updates to the framework. Next, you will learn the full spectrum of traditional machine learning algorithm implementations, along with natural language processing and recommender systems. You’ll gain familiarity with the critical process of selecting machine learning algorithms, data ingestion, and data processing to solve business problems. You’ll see a demonstration of how to build supervised machine learning models such as linear regression, logistic regression, decision trees, and random forests. You’ll also learn how to automate the steps using Spark pipelines, followed by unsupervised models such as K-means and hierarchical clustering. A section on Natural Language Processing (NLP) covers text processing, text mining, and embeddings for classification. This new edition also introduces Koalas in Spark and how to automate data workf | | 出版日期 | Book 2022Latest edition | | 關鍵詞 | Machine Learning; PySpark; Python; Supervised Learning; Unsurpervised Learning; Reinforcement Learning; Re | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4842-7777-5 | | isbn_softcover | 978-1-4842-7776-8 | | isbn_ebook | 978-1-4842-7777-5 | | copyright | Pramod Singh 2022 |
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