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@CORD-ai

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AneeshBose/README.md

Hi there, I'm Aneesh!πŸ‘‹

LinkedIn

I am a Data and Applied Scientist at Microsoft India Development Center. I have completed my undergraduate studies in Computer Science and Engineering from Manipal Institute of Technology with a minor specialization in Intelligent Systems.

  • πŸ”­ I'm currently working on building Copilots using LLMs like GPT-35-Turbo and GPT-4. I also work on Explainable AI (XAI) and Recommender Systems.
  • 🌱 I’m passionate about Natural Language Processing using Deep Learning, Generative AI using Large Language Models and Prompt Engineering.
  • πŸ‘― I’m looking to collaborate on research in Generative AI, LLMs, Information Retrieval and seq2seq tasks like Machine Translation.
  • πŸ’¬ Ask me about data science, competitive programming, machine learning, software engineering and NLP.
  • πŸ“« How to reach me: Gmail
  • πŸ˜„ Pronouns: he/him/his
  • ⚑ Fun fact: I love sports. Represented my school in TT and Badminton, played cricket at district level, lawn tennis at club level and play football and squash in my pastime.

I am fond of competitive programming, but now I do it for fun and to learn new data structures and algorithms. You can find my programming activity below.
Codechef Hackerrank Hackerearth

Aneesh's GitHub stats

Top Langs

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  1. OCRHackathon OCRHackathon Public

    Optical Character Recognition for HackerEarth and Exact Health Sciences

    HTML 4 4

  2. ImageForgeryLocalization ImageForgeryLocalization Public

    Our Image Forgery Localization Implementation for Data Science Hackathon conducted by CSA, IISc.

    Jupyter Notebook 1

  3. SimilarityGraph-WordNet SimilarityGraph-WordNet Public

    Creating a Similarity Graph from WordNet - Lubomir Stanchev

    Shell 1

  4. Page-Replacement-Algorithms Page-Replacement-Algorithms Public

    C

  5. 5-class-sentiment-analyzer 5-class-sentiment-analyzer Public

    Used the official data from a startup(Niki.ai) to predict the sentiment of feedback the company received for its chatbot.

    Jupyter Notebook 1

  6. Semantic-Query-Search-Using-Co-Occurrence-Clustering-in-Word-Graphs Semantic-Query-Search-Using-Co-Occurrence-Clustering-in-Word-Graphs Public

    Scikit-learn implementation of co-occurrence word graph based semantic query search using machine learning and vector space similarity measures.

    Python 2