Raoof Naushad's starred repositories
web-dev-projects
Projects repo for tutorials for my YouTube Channel
matchmaking
Embedding space of names clustered based on their interests using the sentence-transformers all-MiniLM-L6-v2 model
jwt-backend-template
Plug and play jwt apis
DataAnalytics
Explore a diverse array of data analytics techniques across Python, R, SQL, JavaScript, Scala, Julia, and more. Featuring cross-language examples, real-world datasets, and collaborative learning. Join us to enhance your data analytics skills!
ds-algo-pratice
30 days coding challlenge
notepad-plus-plus
Notepad++ official repository
tinder-clone
Tinder Clone -- Implemented using .Net core WebAPI and Angular
rag_with_chroma
A dynamic exploration of LLaMAindex with Chroma vector store, leveraging OpenAI APIs. This repository contains four distinct example notebooks, each showcasing a unique application of Chroma Vector Stores ranging from in-memory implementations to Docker-based and server-based setups.
assignment3
assignment 3 - matchmaking
LLAMA-RAG-Workspace
This repository is dedicated to exploring and implementing the LLAMA index and RAG techniques with OpenAI's tools and resources.
mechanistic_intepreteability
Explore the interpretability of language models with TransformerLens in this repository. We leverage Hugging Face Transformers and the mechanistic interpretability package to reverse engineer the algorithms learned by these models during training, shedding light on their inner workings.
Transformer-Reversed-Integer-Seq2Seq
Explore the essence of Transformer architecture with our Python repository. Featuring a minimalist Seq2Seq Transformer, this educational project focuses on reversing integer sequences. Uncover the fundamentals without external libraries, making it an ideal entry point for understanding Transformers. Start your educational journey today.
PredictiveWebAnalyzer-Logistic-Regression--Data-Classification-Model
"Explore 'WebClassify-LogisticRegression': A concise guide to using logistic regression for website quality prediction. Dive into practical ML insights! 🌐🔍"