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aptos2019

43th place (top2%) Solution for Kaggle APTOS 2019 Blindness Detection

attention-driven-loss

Attention-Driven Loss for Anomaly Detection in Video Surveillance

attention-driven-loss-for-video-anomaly-detection

bengalicharacterrecognition

SILVER MEDAL WINNING Trained Model and Inference for Bengali Character Recognition

codeacademy-projects

course-v3

The 3rd edition of course.fast.ai

deep-matrix-factorization

deeplearning_assignment

This is an implementation of Cats vs Non Cats assignment of neural networks and deep learning on coursera.

diabetic-retinopathy

echo

Python package containing all custom and SOTA mathematical backend algorithms used in Machine Learning.

git_practice

keras-radam

RAdam implemented in Keras & TensorFlow

logistic-reg

Logistic regression from scratch with NumPy

matrix-completion-by-deep-matrix-factorization

The MATLAB code for the algorithm

ntire21_learning_sr_space

CVPR 2021 Challenge on Super-Resolution Space

panda-challenge

radam

On the Variance of the Adaptive Learning Rate and Beyond

sarcasm-detection

sig_math_derivative_calculator

Calculator for UIC SIG Math 2021

srflow

Official SRFlow training code: Super-Resolution using Normalizing Flow in PyTorch

wgan---pytorch-implementation

yelp-recommender-system

In this work, I have created a recommendation system for restaurants using collaborative filtering (CF). The general structure of a recommendation system is that there are users and there are items. Users express explicit or implicit preferences towards certain items. CF thus relies on users' past behavior.