Ashish Jha's repositories
AI_Curriculum
Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.
AV-k8s-placement-app
project folder for ML model deployment using Kubernetes
awesome-edge-machine-learning
A curated list of awesome edge machine learning resources, including research papers, inference engines, challenges, books, meetups and others.
awesome-ml-model-compression
Awesome machine learning model compression research papers, tools, and learning material.
azure-docs
Open source documentation of Microsoft Azure
computervision-recipes
Best Practices, code samples, and documentation for Computer Vision.
E2E_Machine_Learning
An end to end framework for machine learning
educative.io_courses
this is downloadings of all educative.io free student subscription courses as pdf from GitHub student pack
evidently
Interactive reports to analyze machine learning models during validation or production monitoring.
graffitist
Graph Transforms to Quantize and Retrain Deep Neural Nets in TensorFlow.
kubernetes-the-hard-way
Bootstrap Kubernetes the hard way on Vagrant on Local Machine. No scripts.
Machine-Learning-Tutorials
machine learning and deep learning tutorials, articles and other resources
mslearn-ai-vision
Lab files for Azure AI Vision modules
opencv_extra
OpenCV extra data
python_for_microscopists
https://www.youtube.com/channel/UC34rW-HtPJulxr5wp2Xa04w?sub_confirmation=1
Quantization.MXNet
Simulate quantization and quantize aware train for MXNet-Gluon models.
tensorflow
An Open Source Machine Learning Framework for Everyone
TensorFlow2.0-Examples
🙄 difficult algorithm, simple code.
TSFpaper
This repository contains a reading list of papers on Time Series Forecasting/Prediction (TSF) and Spatio-Temporal Forecasting/Prediction (STF). These papers are mainly categorized according to the type of model.
U-Net-Fixed-Point-Quantization-for-Medical-Image-Segmentation
Repository containing code for "U-Net Fixed-Point Quantization for Medical Image Segmentation" paper at MICCAI2019