How to analyze text data for AI and ML with Named Entity Recognition

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About the webinar

Internet is a rich source of data, mainly textual data. But making use of huge quantities of data is complex and time consuming task. NLP can help with this problem through the use of Named Entity Recognition systems. Named entities are terms that refer to names, organisations, locations, values etc. NER annotates texts – marking where and what type of named entities occurred in it. This step significantly simplifies further use of such data, allowing for easy categorisation of documents, analyze sentiments, improving automatically generated summaries etc.

Further, in many industries, the vocabulary keeps changing and growing with new research, abbreviations, long and complex constructions and makes it difficult to get accurate results or use rule-based methods. Named Entity Recognition and Classification can help to effectively extract, tag, index and manage this fast and ever-growing knowledge.

Through this webinar, we will understand how NER can be used to extract key entities from large volumes of text data

What you will learn

How organizations are leveraging Named Entity Recognition across various industries

Live demo - Identify & classify complex terms & with NERC (Named Entity Recognition & Categorization

Best practice to automate machine learning models in hours not months

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Speaker(s) & Panelist(s):


Nisha Shoukath

Co-founder and COO at

COO & Technology leader with over 20 years of experience in Product development, Artificial Intelligence and Machine Learning business strategy and acceleration. Consultant to Fortune 100 organizations across IT, Telecom, Manufacturing, Healthcare, Construction, Pharmaceuticals, Retail, Biotechnology, Banking and Insurance sectors to deliver business impact.


Shruti Tanwar

Lead - Data Science

Extensive experience working at the forefront of innovative projects, building future tech using Machine Learning and Artificial Intelligence.


Bikash Kumar Sharma

Chief Technology Officer at

CTO & Software Architect with close to 15 years of experience whose passion lies in building great products while enabling others to perform their roles more effectively. Lead at the forefront of innovative projects, building future tech using Machine Learning and Artificial Intelligence.