7enTropy7/7enTropy7.github.io
I'm Batman.
I always learn from mistakes of others who take my advice.
I'm Batman.
A few lines of code using which I can hack your computer. I mean it literally :P
This is how you teach a dumb bot to walk on two feet.
A Post-Quantum Encryption Algorithm
An LSTM based Eminem Rap generator.
A Federated Learning based architecture for training a PPO agent that learns to play Gin Rummy.
My experiments with Nexys4 DDR Artix-7 FPGA Board
Code for an Indoor Navigation System developed during DevJams'19 Hackathon
This is a C++ program that implements the Layer-Wise method to solve a 3×3×3 Rubik’s Cube in under 800 lines of code.
Developed a highly customizable OpenAI gym environment and trained a stable_baselines3 PPO agent. Used the expert agent for Imitation Learning with DAgger
A Q-Learning agent which finds the optimum escape route.
R.I.P - RSA_cryptography (1977-2019)
A Deep Q Network A.I agent that plays the old classic Nokia Snakes Game!
An autonomous robot capable of traversing alien environments and sending relevant data retrieved back to the user.
Python client for federated and distributed computing
Raven Distribution Framework's Deep Learning Library
Ravop is one of the crucial build blocks of Ravenverse. It is a library for requesters to create and interact with ops, perform mathematical calculations, and write algorithms.
The foundation for any Machine Learning or Deep Learning Framework. Simply put, it is more like a decentralized calculator, comparable to a decentralized version of the IBM machines the were used to launch the Apollo astronauts. Apart from building ML/DL frameworks, a lot more can be done on it, such as maximizing yield on your favorite defi protocols like Compound and more!
A genetically evolved dinosaur that is scared of Cactus!
Developed using Socket Programming and Tkinter for GUI
My experiments with Atari games
This code can see and solve sudoku puzzles.
Raven Distribution Framework's Javascript Library
RavML is the machine learning library based on RavOp. It contains implementations of various machine learning algorithms like ordinary least squares, linear regression, logistic regression, KNN, Kmeans, Mini batch Kmeans, Decision Tree classifier, and Naive Bayes classifier
Top 8 Finalist Hackathon project and Urban Track Winner at HackMIT 2020
An efficient NEAT implementation on a multi-agent Pong environment