-
ML Scientist - 2 @ PayPal Inc.
- San Francisco Bay Area
- https://katreparitosh.github.io/
- in/paritoshkatre
Lists (4)
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Starred repositories
Large World Model -- Modeling Text and Video with Millions Context
The lazier way to manage everything docker
A box of core libraries for recommendation model development
List of projects related to Natural Language Processing (NLP) that make a geek smile for they exist
ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP
Welcome to the LLMs Interview Prep Guide! This GitHub repository offers a curated set of interview questions and answers tailored for Data Scientists. Enhance your understanding of Large Language M…
[ACL 2024] An Easy-to-use Knowledge Editing Framework for LLMs.
Tips and tricks for working with Large Language Models like OpenAI's GPT-4.
đź“‹ A list of open LLMs available for commercial use.
🦜🔗 Build context-aware reasoning applications
Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.
DSPy: The framework for programming—not prompting—language models
Machine Learning Engineering Open Book
An open source implementation of OpenAI's ChatGPT Code interpreter
CLI platform to experiment with codegen. Precursor to: https://lovable.dev
The missing star history graph of GitHub repos - https://star-history.com
Multi-dimensional Analytics Project on Road Accidents of India.
Federated learning study for customer path prediction
Chat with your database or your datalake (SQL, CSV, parquet). PandasAI makes data analysis conversational using LLMs and RAG.
A curated list of awesome Recommender System (Books, Conferences, Researchers, Papers, Github Repositories, Useful Sites, Youtube Videos)
Introduction to Applied Process Mining with Python and R notebooks.
MS-Apriori is used for frequent item set mining and association rule learning over transactional data.
Python implementation of the Frequent Pattern Growth algorithm
This tutorial meant as an introduction to process mining using PM4PY library in Python