RAHUL SHARMA's repositories
Blockchain_for_user_auth
It is a project with an idea o using block chain for user authentication in various scenarios
Auto_route-Practice
Practice Application for POC on auto-route package
awesome-neuroscience
A curated list of awesome neuroscience libraries, software and any content related to the domain.
awesome-public-datasets
A topic-centric list of HQ open datasets.
Backend-for-secure-chat-channel
Protocol for implementing secure chat channel implemented using python (integration with blockchain)
BLOCKCHAIN-COMPLETE-
This is complete block chain implementation using python with all the block chain functionalities with a custom cryptocurrency and also a demo implementation of smart contract for ICO concept.
End-to-End-ML
This repository is for all of my ML and AI learning. This will become a portal to my extensive academic journey.
bomberman_game
Python game of Bomber_man using Reinforcement learning
bomberman_rl_RBN
Final-project base model for Machine Learning subject.
ComputerVision-24
Final term project for computer vision
Credit_card_fraud_detection
rahul2227/Credit_card_fraud_detection
Deep-Learning-Papers-Reading-Roadmap
Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!
DeformationPyramid
[NeurIPS 2022] Non-rigid Point Cloud Registration with Neural Deformation Pyramid
lepard
[CVPR 2022, Oral] Learning Partial point cloud matching in Rigid and Deformable scenes
Medic-Meditation-App
Calming and UI intensive Flutter based application for meditation
ml-road
Machine Learning Resources, Practice and Research
Optimized-BCI
An optimal BCI for motor imagery classification on dataset BCI competition IV and Generalizable BCI DATASET
PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
Recommendation_system
Amazon_Recommendation_system
SIMPLE_BLOCKCHAIN_CPP
It is a simple Blockchain representation and mining technique using cpp made on visual studio.
titanic_analysis
Titanic_analysis
Twitter_sentimental_analysis
This is a sentimental analysis of tweets using machine learning(algorithm = Naive_bayes) made using python.