Building the opensource standard for testing and evaluating LLM application (YC W24)https://docs.ragas.io

Building ML pipelines for DeepInsight.

Mining Short Text Messages and Alternative data for credit underwriting.

mljar automates the common way to build complete Machine Learing Pipeline to find the best ML models for your data!

- Developed an end to end pipeline for credit underwriting model using gradient boosting algorithm.- Cluster identification of short text messages. ( NLP - Unsupervised)- Worked in named entity extraction from short text messages to enhance ML models for credit scoring.

- Responsible for Data strategy and End to End Machine learning and Natural Language processing.- Developed several Classification, Clustering, and Named Entity Recognition models in TensorFlow.- Deployed the projects in the Google Cloud platform using AI platform services.

- Worked as a freelance Data science content creator. - Wrote a series of articles featuring different Machine learning and Deep learning techniques.Some of the popular articles,- https://neptune.ai/blog/document-classification-small-datasets- https://neptune.ai/blog/tabular-data-binary-classification-tips-and-tricks-from-5-kaggle-competitions

I am one of the lead organizers and tutor of School of Ai, Kochi. We organize and conduct workshops on various topics in Data science,Machine learning and Deep learning.

I am active contributor and learner at Kaggle which is the world's largest Data science and Machine learning community.It has around 95k users.I am ranked in kaggle Top #100.

A regular contributor in Kaggle competitions and projects.

Working as the Intern Data scientist for Concepts.Ai team.I am currently working on a Recommendation engines,Reciprocity recommendation engines which is used for people to people recommendation.

i was a part of project on alumni reach web application.