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🔭 I’m currently working at OpenLocus.ai and working on DiscoveryBench - A benchmark for evaluating LLMs and Agentic systems where on given a set of hypotheses, a high-level workflow and a real-world dataset, how well does the system explore and generate new insights?
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🔭 I have worked in the ML engineering team and performed 200+ experiments on generating insights using a multi-agent framework like Autogen and have been acknowledged in the paper on Data-driven discovery using LGMs published at the International Conference of Machine Learning (ICML).
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🌱 I’m currently learning Spring Boot, Flask.
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🖥️I have participated in multiple hackathons and have created projects like Attornify, Transverse etc.
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💬 Ask me about AutoGen multi-agent framework, Data-driven discovery using LLMs, RAG and Backend System Design
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📫 You can can reach me at vora.tirth09@gmail.com
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⚡ Fun fact I learn very fast and come up with very unique perspectives on solving problems!
I am extremely curious, learn quickly and want to build LLM applications and robust system designs.
I try to explore 'how cool things work'!
- Mumbai
- in/tiirthvora
Highlights
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Data_Extraction_and_NLP
Data_Extraction_and_NLP PublicAutomated scraping article text from 100 URLs along with sentiment and readability analysis in each
Python 1
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Ettarra-Sales-Analysis-and-Backend
Ettarra-Sales-Analysis-and-Backend PublicI created this backend in a hackathon where I performed exhaustive analysis of a coffee-chain, and created a backend for sending visualization data to the frontend
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Regression-with-Deployment
Regression-with-Deployment PublicI've made this complete end-to-end project with the aim of learning how to deploy a machine learning model. Here I pre-processed, explored and statistically examined the Boston_house_price dataset …
Jupyter Notebook
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