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alphabet-inc.-googl-stock-prices-using-sklearn

awesome-deep-learning-papers

The most cited deep learning papers

basic-text-cleaning

Discusses various text cleaning tools

denoising_bert

deployonstreamlit

emotion-classification

The repo uses self-attention and cross-attention over MELD dataset for classifying emotions in a conversation

fewshottext

Library of various Few-Shot Learning frameworks for text classification

grammarly-for-transcriptions

This is a grammar corrector for speech-transcriptions, written-transcriptions, (.wav) file's transcriptions.

ket

The PyTorch code for paper "Knowledge-Enriched Transformer for Emotion Detection in Textual Conversations"

knn-implementation-from-scratch

K-Nearest Neighbour(over breast cancer data set),implemented from scratch

linear-regression-using-matrix-

Linear Regression with matrix transpose and inverse

linear-regression-using-sgd

linear_regression-using-bgd

Linear Regression with batch gradient descent

lm-bff

ACL'2021: LM-BFF: Better Few-shot Fine-tuning of Language Models

logistic-regression-using-ann

Implementation of Logistic Regression using Neural Network (from scratch)

longformer

Longformer: The Long-Document Transformer

paraphrase-identification

Assignment

rishabh

sentbert_finetune

An architecture for fine_tuning BERT

simple_snake

smashrnn

It uses 3-Stage, 3 levels encoder (word_level, sent_level, para_level) to encode the input using GRUs. Further , it uses Siamese network (of MeshRNNs) to learn the similarity between the documents.

text_classification-using-nltk

transformer-encoder-

Pytorch implementation of Transformer encoder.