I am Deependra
deepenmi Goto Github PK
Name: Deependra Mishra
Type: User
Company: Washington University in St. Louis
Bio: Staff Scientist - Hyperspectral Imaging Research | Machine Learning | Medical Imaging | Deep Learning
Name: Deependra Mishra
Type: User
Company: Washington University in St. Louis
Bio: Staff Scientist - Hyperspectral Imaging Research | Machine Learning | Medical Imaging | Deep Learning
:memo: An awesome Data Science repository to learn and apply for real world problems.
The most cited deep learning papers
An awesome list of high-quality open datasets in public domains (on-going).
A curated list of awesome Python frameworks, libraries, software and resources
Bioinformatics with Python Cookbook Second Edition, published by Packt
MATLAB toolbox package for the exploration of computer vision and image processing
CVIPtools is designed for the exploration of computer imaging by allowing you to interactively experiment with computer imaging techniques, functions and algorithms. It is designed to be used for education, as well as for research and development. It is an on-going project developed at Southern Illinois University at Edwardsville in the Computer Vision and Image Processing Laboratory under the direction of Scott E Umbaugh, PhD.
Continually updated data science Python notebooks: Deep learning (TensorFlow, Theano, Caffe), scikit-learn, Kaggle, big data (Spark, Hadoop MapReduce, HDFS), matplotlib, pandas, NumPy, SciPy, Python essentials, AWS, and various command lines.
Self Learning
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Hands-on Deep Reinforcement Learning, published by Packt
This is a special repo for my GitHub profile that tells about my lazy journey of coding, where semicolons detour, comments nap, and debugging strolls leisurely. Welcome to the realm where efficiency meets the art of doing just enough, and procrastination is a feature, not a bug. Just playing around with bits and bytes.
Personal blog
Deep Learning with TensorFlow, Keras, and PyTorch
Deep learning model to detect fire and smoke in an image
This repository contains the source code for the paper First Order Motion Model for Image Animation
General texture analysis package for texture and entropy/statistical complexity analysis methods
The Open Source Data Science Masters
A library for hyperspectral image analysis using scikit-learn.
Statistical hypothesis tests in python
Machine learning basics using colab
Source code for 'Monetizing Machine Learning' by Manuel Amunategui and Mehdi Roopaei
Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler; for Python, R, Julia, Scala, Go, Javascript and more
Natural Language Processing and Regular Expression Practice
A Python package for data analysis with permutation entropy and ordinal networks methods.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.