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Name: Utathya
Type: User
Name: Utathya
Type: User
This is my reading list for my PhD in AI, NLP, Deep Learning and more.
An open-source NLP research library, built on PyTorch.
This repository contains all the papers which I read and annotate. The papers are mostly RL focused, however, expect some deviations.
Contains all research papers read since the end of July 2020 :+1:
This repository is a comprehensive collection of research papers, annotations, and concise summaries in the field of Natural Language Processing (NLP). It focuses on machine learning and deep learning techniques, providing valuable resources for NLP enthusiasts and researchers.
This repo contains annotated research papers that I found really good and useful
Approaching (Almost) Any Machine Learning Problem
Art to Image Style Transfer using Keras and Tensorflow.
A curated list of awesome Deep Learning tutorials, projects and communities.
A one stop repository for generative AI research updates, interview resources, notebooks and much more!
List of datasets, codes, and contests related to remote sensing change detection
Papers about deep learning ordered by task, date. Current state-of-the-art papers are labelled.
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
Jupyter notebooks for the code samples of the book "Deep Learning with Python"
Summaries and notes on Deep Learning research papers
These are Some useful ebook
Methods with examples for Feature Selection during Pre-processing in Machine Learning.
:books: Freely available programming books
A collection of scientific methods, processes, algorithms, and systems to build stories & models. This roadmap contains 16 Chapters, whether you are a fresher in the field or an experienced professional who wants to transition into Data Science & AI
Hands-On Genetic Algorithms with Python, Published by Packt
A repo for Python learning
A pattern-based approach for learning technical interview questions
Programming Assisgnments for Machine Learning using various algorithms in Octave/ Matlab.
The code from the Machine Learning Bookcamp book and a free course based on the book
A curated list of papers, theses, datasets, and tools related to the application of Machine Learning for Software Engineering
Must-read papers on model editing.
Monk is a low code Deep Learning tool and a unified wrapper for Computer Vision.
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.