Hasham Ul Haq is a Data Scientist at John Snow Labs, and an AI scholar and researcher at PI School of AI. During his carrier, he has worked on numerous projects across various sectors, including healthcare. At John Snow Labs, his primary focus is to build scalable and pragmatic systems for NLP, that are both, production-ready, and give SOTA performance. In particular, he has been working on Natural Language Inference, disambiguation, Named Entity Recognition, and a lot more! Hasham also has an active research profile with a publications in NeurIPS, AAAI, and multiple scholarship grants and affiliations.
Prior to John Snow Labs, he was leading search engine and knowledge base development at one of Europe’s largest telecom providers. He has also been mentoring startups in computer vision by providing trainings and designing ML architectures.
Entity Resolution is the process of predicting UMLS codes for medical concepts. While processing medical text, this process relies heavily on the concepts identified by NER models. NER models at...
In this video, we will see how to train an Entity Resolver for SNOMED codes from scratch. We will start from the SNOMED graph as downloaded from the internet, going...
This video dives deep into the basic concepts of Spark NLP Annotators, Annotations and Pipelines. It will give you solid foundations into how Spark NLP works and lets you create...
Demos
