About

Shikha Agarwal is a Machine Learning enthusiast with a passion for Natural Language Processing (NLP) and Deep Learning. She is currently seeking full-time positions in the field of Machine Learning, having gained extensive experience working on projects such as Named Entity Recognition (NER), sentiment analysis in the NLP domain, and image retrieval and detecting diabetic retinopathy in computer vision domain. Shikha is currently working on developing a Question Answering system for open-ended and unanswerable questions. She has also worked on a research project with Professor McCallum and CZI team in solving entity recognition and entity linking jointly for biomedical papers. Prior to her work in Machine Learning, Shikha worked as a Software Developer at Gwynniebee, an e-commerce rental service startup. This experience has helped her mature in conceptualizing, designing, and implementing scalable systems. Shikha possesses a Master of Science degree in Computer Science from the University of Massachusetts, where she is currently working as a Grader for Probabilistic Graphical Models (688). She has also worked as a Grader for COMPSCI 682 (Deep Learning) at the University of Massachusetts. Shikha's technical skills include programming languages such as Python, Java, C/C++, and tools and frameworks such as Tensorflow, Pytorch, Linux, Maven, REST, and Git. She has experience with AWS, Scikit, Pandas, MySQL, Neural Networks, Search, Reinforcement Learning, Naive Bayes, CNN, Parts-of-speech, and Elastic Search. In summary, Shikha Agarwal is a highly skilled Machine Learning professional with a diverse range of experience in NLP, Deep Learning, and Computer Vision. Her technical skills and experience make her a valuable addition to any organization seeking to leverage the power of Machine Learning.