Natural Language Processing (NLP) will Revolutionize Industry

ACM Data Science SIG talk series

SK Reddy, https://www.linkedin.com/in/sk-reddy/

SCHEDULE

6:30 register, network, food

7:00 – 7:10  ACM introduces future events, speaker

7:10 – 8:30  Presentation

9:00  hard time for all to be out

DESCRIPTION:  Processing text is a little more difficult talk than processing numbers. At the same time, there is a lot more wisdom trapped in structured and unstructured documentation. The product documentation, online blogs, structured reports in different languages need to be assimilated to comprehend, answer questions and summarize. Similarly unstructured document sources like Quora, Stackoverflow, patient report narratives, news reports provide additional source of information distributed across multiple locations. NLP can solve the problem of collection, analysis, answer questions, summarize, translate and comprehend.

I would like to talk about the emerging solutions in NLP to process text for summarization, language translation, answer questions and comprehension.

BIO:

SK Reddy is the Chief Product Officer AI & ML in Digitalist Group (www.digitalistgroup.com). He is also an AI and ML expert and a blogger (check his LinkedIn). SK founded two tech startups.  He is a frequent speaker in conferences and meetups. 

Below are some links to his profile.  

• LinkedIn

• Conference speaker:

• Global Big Data Conference 2017

• AI Frontiers 2017

• QCon 2017

• Big Data Bootcamp 2017

• AI Europe 2017

• YouTube Videos

• Language Translation using NNs

• Teaching Computers to Comprehend

• Text Summarization techniques in Deep Networks

• NLP workshop in Global Big Data Conf (Part 1, 2, 3)

• Techniques for efficient summarization text using Neural Networks

• Blogs:

1. How to make Neural Networks “describe” images

2. 9 Months of NLP in 4 hours

3. The Magic of Language Translation using Neural Networks

4. Summarization and Abstraction using Deep Networks

5. Teaching Computers to Comprehend Mahabharat

6. Opinion mining on large datasets

7. Sentiment Analysis using Neural Networks

8. Problem solving three different ML approaches

9. Performance comparison between Decision Tree and SVM

10. What Great Product Managers do!!

11. My Experiments with Innovation

• Github