Jump to content
Welcome Guest!

Join us now to get access to all our features. Once registered and logged in, you will be able to create topics, post replies to existing threads, give reputation to your fellow members, get your own private messenger, and so, so much more. It's also quick and totally free, so what are you waiting for?

This site uses cookies! Learn More

This site uses cookies!

For providing our services, we do use cookies.
But get used, this is what most of modern web do!
However we have to warn you since we are obligated to so due to EU laws.

By continuing to use this site, you agree to allow us to store cookies on your computer. :)
And no, we will not eat your computer nor you will be able to eat those cookies :P

  • Announcements

    • xZero

      Service Recovery Status [LIVE]   01/12/2018

      Track our system status and recovery on actively updated page: https://www.elite7hackers.net/topic/340999-service-recovery-status/


This topic is now archived and is closed to further replies.


Text Mining & Natural Language Understanding at Scale Training Video

Recommended Posts

Text Mining & Natural Language Understanding at Scale Training Video
2016-07-27 | SKU: 02392 | .MP4, AVC, 1000 kbps, 1280x720 | English, AAC, 128 kbps, 2 Ch | 2.25 hours | 871 MB
Instructors: David Talby, Claudiu Branzan

A text mining system must go way beyond indexing and search to appear truly intelligent. First, it should understand language beyond keyword matching. For example, it should be able to distinguish the critical difference between "Jane has the flu" and "Jane had the flu when she was 9". Second, it should be capable of making likely inferences even if they're not explicitly written.For example, inferring that Jane may have the flu if she has had a fever, headache, fatigue, and runny nose for three days. And third, it should do its work as part of a robust, scalable, efficient and easy to extend system. This course teaches software engineers and data scientists how to build intelligent natural language understanding (NLU) based text mining systems at scale using Java, Scala and Spark for distributed processing.

* Learn the meaning of natural language understanding (NLU) and its use in text mining

* Discover how to build a natural language processing (NLP) pipeline within a big data framework

* Recognize the differences between NLP pipelines and other approaches to semantic text mining

* Learn about standard UIMA annotators, custom annotators, and machine learned annotators

* Discover how different types of annotators are composed into a text processing pipeline

* Use machine learning to generate annotators and apply them within a data pipeline

* See pipeline architectures that incorporate Kafka, Spark, SparkSQL, Cassandra, and ElasticSearch

Buy Premium From My Links To Get Resumable Support,Max Speed & Support Me
Download ( NitroFlare )

Download ( Uploaded

Download ( Rapidgator )

[b]Download (BigFile)[/b]

Share this post

Link to post
Share on other sites