O’Reilly – Building Pipelines for Natural Language Understanding with Spark

O’Reilly – Building Pipelines for Natural Language Understanding with Spark
English | Size: 1.14 GB
Category: Tutorial

Building Pipelines for Natural Language Understanding with Spark
A hands-on guide to machine learning annotators, topic modeling, and deep learning for text mining

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.

The course will use sample of posts from the subreddit /r/WritingPrompts, which contains short stories and comments about the short stories.
The course has four parts:
1. Building a natural language processing and entity extraction pipeline on Scala & Spark
2. Machine Learning Applications for Statistical Natural Language Understanding at Scale
3. Topic Modeling on Natural Language with Scala, Spark and MLLib
4. Deep Learning Applications for Natural Language Understanding with Scala, Spark and MLLib

You will learn how use Apache Spark to process text with annotations, use machine learning with your annotations, create and use topic models, create and use a word2vec model.

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