mayeshmohapatra Goto Github PK

100-days-of-ml-code

100 Days of ML Coding

2018-05-fentanyl-and-cocaine-overdose-deaths

Data, analytic code, and findings supporting BuzzFeed News's analysis of fentanyl and cocaine overdose deaths.

algorithmsuse

Common Algorithms which are usually taught in Data Structures and Algorithms courses.

basicml

A collection of basic ML Projects.

c-plus-plus

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

chestxrayclassification

Implementation of DenseNet-121 on the CheXpert Dataset.

cnns-from-scratch

A collection of State of the Art Convolutional Neural Network based architectures which are implemented from the ground up.

codes-for-lane-detection

Learning Lightweight Lane Detection CNNs by Self Attention Distillation (ICCV 2019)

cs7015_2019

CS7015: Deep learning, IIT Madras. This repository contains code for all the assignments completed as a part of the course CS7015 Deep Learning at IIT Madras during the Jan-May semester of 2019 and some other useful material.

cv-tasks

A repository containing simple computer vision tasks, mostly implemented without any ML in them, using only computer vision techniques

data-science

:bar_chart: Path to a free self-taught education in Data Science!

diseasedetectioninappleleaves

dl_boilerplate

A boilerplate to get started with a Deep Learning project (Vision)

ema-vfi

[CVPR 2023] Extracting Motion and Appearance via Inter-Frame Attention for Efficient Video Frame Interpolatio

everything

An index of all our open-source data, analysis, libraries, tools, and guides.

hacktoberfest_2020

Learn, Contribute, Win

imagesegmentation-unet

mayeshmohapatra

Config files for my GitHub profile.

python-basics

Basics for learning Python

pytorch-grad-cam

Advanced AI Explainability for computer vision. Support for CNNs, Vision Transformers, Classification, Object detection, Segmentation, Image similarity and more.

researchpapers

A list of research papers that I have read so far and recommend to other Deep Learning enthusiasts such as myself.

sahi

Framework agnostic sliced/tiled inference + interactive ui + error analysis plots

stanford-cme-106-probability-and-statistics

VIP cheatsheets for Stanford's CME 106 Probability and Statistics for Engineers

stylegan-tensorflow2

StyleGAN - TensorFlow 2.0 implementation compatible with the official code

trumpworld

TrumpWorld data as CSV and GraphML files

voice-cloning

weq

weq-website