國立虎尾科技大學 |

Next-Generation Machine Learning with Spark = Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Next-Generation Machine Learning with Spark/ by Butch Quinto.
其他題名:	Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /
作者:	Quinto, Butch.
面頁冊數:	XIX, 355 p. 67 illus.online resource. :
Contained By:	Springer Nature eBook
標題:	Big Data. -
電子資源:	https://doi.org/10.1007/978-1-4842-5669-5
ISBN:	9781484256695

Next-Generation Machine Learning with Spark = Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /
Quinto, Butch.

Next-Generation Machine Learning with SparkCovers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /[electronic resource] :by Butch Quinto. - 1st ed. 2020. - XIX, 355 p. 67 illus.online resource.

Chapter 1: Introduction to Machine Learning -- Chapter 2: Introduction to Spark and Spark Mllib -- Chapter 3: Supervised Learning -- Chapter 4: Unsupervised Learning -- Chapter 5: Recommendations -- Chapter 6: Graph Analysis -- Chapter 7: Deep Learning.-.

Access real-world documentation and examples for the Spark platform for building large-scale, enterprise-grade machine learning applications. The past decade has seen an astonishing series of advances in machine learning. These breakthroughs are disrupting our everyday life and making an impact across every industry. Next-Generation Machine Learning with Spark provides a gentle introduction to Spark and Spark MLlib and advances to more powerful, third-party machine learning algorithms and libraries beyond what is available in the standard Spark MLlib library. By the end of this book, you will be able to apply your knowledge to real-world use cases through dozens of practical examples and insightful explanations. You will: Be introduced to machine learning, Spark, and Spark MLlib 2.4.x Achieve lightning-fast gradient boosting on Spark with the XGBoost4J-Spark and LightGBM libraries Detect anomalies with the Isolation Forest algorithm for Spark Use the Spark NLP and Stanford CoreNLP libraries that support multiple languages Optimize your ML workload with the Alluxio in-memory data accelerator for Spark Use GraphX and GraphFrames for Graph Analysis Perform image recognition using convolutional neural networks Utilize the Keras framework and distributed deep learning libraries with Spark .

ISBN: 9781484256695

Standard No.: 10.1007/978-1-4842-5669-5doiSubjects--Topical Terms:

1017136
Big Data.

LC Class. No.: QA76.9.B45

Dewey Class. No.: 005.7

Next-Generation Machine Learning with Spark = Covers XGBoost, LightGBM, Spark NLP, Distributed Deep Learning with Keras, and More /
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