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Machine Learning Researcher
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Simple-LlamaIndex-Agent
December 26, 2024 – December 26, 2024
A FastAPI-based application that combines a Retrieval-Augmented Generation (RAG) system with an intelligent agent for enhanced information retrieval and query handling.
View ProjectMedical-Prescription-Extractor
December 25, 2024 – December 25, 2024
An AI-powered application that extracts and structures medical prescription information.
View ProjectRAG-Video-Transcription-Q-A-Assistant
December 25, 2024 – December 25, 2024
The RAG Video Transcription System uses Retrieval Augmented Generation with Elasticsearch to extract, process, and query video transcripts.
View ProjectImage-Classification-Capsule-Network
July 24, 2024 – July 26, 2024
Image-Classification-Capsule-Network — GitHub repository
View Projectravikumarmn.github.io
January 28, 2024 – May 29, 2024
ravikumarmn.github.io — GitHub repository
View ProjectTransformer-Based-Languge-Model
April 11, 2023 – April 20, 2023
Transformer based charcter level language model.
View Projectsimilar-research-papers-predictor
December 10, 2022 – December 18, 2022
Results the top similar research papers in NeurIPS-2022
View ProjectLearning-NLP-with-PyTorch
October 22, 2022 – December 16, 2022
Learning Natural Language Processing Using Pytorch.
View ProjectFeedback-Prize---Predicting-Effective-Arguments
July 22, 2022 – July 24, 2022
Goal of the Competition The goal of this competition is to classify argumentative elements in student writing as "effective," "adequate," or "ineffective." You will create a model trained on data that is representative of the 6th-12th grade population in the United States in order to minimize bias. Models derived from this competition will help pave the way for students to receive enhanced feedback on their argumentative writing. With automated guidance, students can complete more assignments and ultimately become more confident, proficient writers. This competition will comprise two tracks. The first track will be a traditional track in which accuracy of classification will be the only metric used for success. Success on this track will be updated on the Kaggle leaderboard. Prize money for the accuracy-only, “Leaderboard Prize” track will be $25,000. The second track will measure computational efficiency in which efficiency is determined using a combination of accuracy and the speed a
View ProjectCultural Fit Analysis
The candidate's project portfolio shows a strong inclination towards individual, personal projects, which might indicate a preference for independent work. The diversity of projects within the ML/NLP domain suggests a strong interest and self-motivation in the field. However, without team-based project experience or work history, it's difficult to assess collaboration or broader cultural fit.
Soft Skills & Operational Fit
Insufficient data to assess soft skills or operational fit. No psychometric test results or interview feedback provided.