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a-journey-into-convolutional-neural-network-visualization-

A journey into Convolutional Neural Network visualization

albumentations

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

apex

A PyTorch Extension: Tools for easy mixed precision and distributed training in Pytorch

caltech-birds-classification

This repo includes code (written in Python) for Caltech-UCSD Birds-200-2011 dataset classification. I have used PyTorch Library for CNN's. You can download the dataset here http://www.vision.caltech.edu/visipedia-data/CUB-200-2011/CUB_200_2011.tgz

computervision

Compuetr Vision related stuff

createimageoverlaysanddepthmask

csharpshooter

dali

A library containing both highly optimized building blocks and an execution engine for data pre-processing in deep learning applications

data-structures-and-algorithms

This repository contains data structures and algorithm implemented in C#.

deeplearning

My deep learning projects

deepspeed

DeepSpeed is a deep learning optimization library that makes distributed training easy, efficient, and effective.

densedepth

High Quality Monocular Depth Estimation via Transfer Learning

developer-roadmap

Interactive roadmaps, guides and other educational content to help developers grow in their careers.

e4p2

EVA 4 Phase 2 assignments

eip

EIP Work

emlo

EMLO

era

eva

EVA assignments

fast-style-transfer

TensorFlow CNN for fast style transfer ⚡🖥🎨🖼

github-readme-stats

:zap: Dynamically generated stats for your github readmes

imgaug

Image augmentation for machine learning experiments.

mirror

Visualisation tool for CNNs in pytorch

mobileneta2

Transfer learning use Mobilenet_V2 for custom images and deploying model to AWS Lambda

monodepth

Unsupervised single image depth prediction with CNNs

monodepth2

Monocular depth estimation from a single image

pytorch-docker-flask

pytorch-flask-starter

🐍+🔥This project is aimed to help Pytorch machine learning developers to quickly build a Flask web app in a Docker container ready to be deployed.

pytorchdeployment

Deploy our PyTorch model with Flask and Heroku. Create a simple Flask app with a REST API that returns the result as json data, and then deploy it to Heroku. Here we will do image classification, and we can send images to our heroku app and then predict it with our live running app.

pytorchtricks

Some tricks of pytorch... :star:

system-design

Learn how to design systems at scale and prepare for system design interviews