The problem Extractive Text Summary Generation and NER solves

Automated summary generation of text using Python, GloVe algorithm, NLP and statistical modelling resulting in the summary of size 20% of original document. Trained an NLP pipeline for entity recognition like date and time, currencies, organizations,
person and locations out of resumes, research documents, articles, blogs, webpages etc.

Challenges I ran into

SpaCy provides a default Named Entity Recognition NLP pipeline to recognize the entities, but it is not very efficient. Developed and trained a custome NLP Named entity recognition pipeline model over the annotated data of text sentences and job resume samples.