Sriharsha-hatwar

Clothing-Fashion-Extraction

Clothing Fashion Extraction from Music Videos or any videos of the kind.

Semantic-similarity

Finding Semantic Similarity between two Sentences using Semantic nets and Corpus statistics

Advanced-Algorithms-and-Data-Structures

Implemenation of some of the well known data structures and algorithms applied to it. (Suffix trees, B-trees and AVL trees)

albumentations

fast image augmentation library and easy to use wrapper around other libraries

BasicBERT

Metaphor Detection via Explicit Basic Meanings Modelling. Presenting at ACL 2023.

BIG-bench

Beyond the Imitation Game collaborative benchmark for enormous language models

CALM-hf

Implementation of the paper : https://arxiv.org/abs/2401.02412

DACCS-601-Ch8

dask

Parallel computing with task scheduling

Tweet-Sentiment-Span-Extraction

This was the solution that we used to achieve top 8% private leaderboard in kaggle.

dragnet

Just the facts -- web page content extraction

ecc

ent-res-feedback

End-to-end entity resolution with feedback

extractnet

A fork of Dragnet that also extract author, headline, date, keywords from context, as well as built in metadata extraction all in one package

ludwig

Data-centric declarative deep learning framework

ml-nfts

my-first-blog

numpy

The fundamental package for scientific computing with Python.

pandas

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

pytorch

Tensors and Dynamic neural networks in Python with strong GPU acceleration

rl-from-scratch

rl-sentence-compression

Code for the ACL 2022 paper "Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement Learning"

scikit-learn

scikit-learn: machine learning in Python

Sriharsha-blog

This repo maintains my blog

Sriharsha-hatwar.github.io

temp

transformers

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

wilds

A machine learning benchmark of in-the-wild distribution shifts, with data loaders, evaluators, and default models.

Without-A-Hitch

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