The Low Spark of High Heeled Boys marked the commercial and artistic apex of the second coming of Traffic, which had commenced in 1970 with John Barleycorn Must Die. The trio that made that album had been augmented by three others (Ric Grech, Jim Gordon, and "Reebop" Kwaku Baah) in the interim, though apparently the Low Spark sessions featured varying combinations of these musicians, plus some guests…
Whether you’re a programmer with little to no knowledge of Python, or an experienced data scientist or engineer, this Learning Path will walk you through natural language processing, using both Python and Scala, and show you how to implement a range of popular tools including Spark, scikit-learn, SpaCy, NLTK, and gensim for text mining.
Spark is a powerful distributed computing engine for big data, and has emerged as a leading tool in the industry with its focus on improving efficiency and usability. Tutorials and sessions in this Learning Path will teach you about Spark 2.0 libraries, tips and tricks for deploying Spark in production and at scale, and how to get up and running with Spark to write your own Spark applications.
The course is designed for engineers and data scientists who have some familiarity with Scala, Apache Spark, and machine learning who need to process large natural language text in a distributed fashion.We will use sample of posts from the subreddit /r/WritingPrompts, which contains short stories and comments about the short stories.The course has four parts1. Building a natural language processing and entity extraction pipeline on Scala & Spark2.
Spark is one of today’s most popular distributed computation engines for processing and analyzing big data. This course provides data engineers, data scientist and data analysts interested in exploring the technology of data streaming with practical experience in using Spark. You’ll learn about the Spark Structured Streaming API, the powerful Catalyst query optimizer, the Tungsten execution engine, and more in this hands-on course where you’ll build small several applications that leverage all the aspects of Spark 2.0. While not a requirement, the course works best for those with some Scala experience.
Data analysts familiar with R will learn to leverage the power of Spark, distributed computing and cloud storage in this course that shows you how to use your R skills in a big data environment.