Computer vision code to detect Neutrophil Extracellular Traps (NETs) in an array of 1024 wells

Real-Time Ergodic Control

My personal website

Repository containing the codes that were used in the paper "Multi-agent Ergodic Coverage with Obstacle Avoidance"

nanoGPT style version of Llama 3.1

The first real AI developer

Adversarial attacks in consensus-based multi-agent reinforcement learning

Using GAN to generate Terrain from LiDAR data

Finance application that provides more than 60 different alternative data to retail investors

An offline deep reinforcement learning library

An implementation of an OpenAI gym environment for EPRI OpenDSS, using OpenDSS's native Python COM interface.

Image restoration with neural networks but without learning.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

🏀🤖🏀 AI web app and API to analyze basketball shots and shooting pose.

Hands-on Deep Reinforcement Learning, published by Packt

A toolkit for reproducible reinforcement learning research.

A hyperparameter optimization framework

TensorFlow (Python API) implementation of Neural Style

Cracking the Coding Interview in Python 3. The solutions all have detailed explanations with visuals.

A comprehensive guide of how to make publication-ready figures in python

Reinforcement learning tutorials

Lessons learned the hard way through over 30+ data science interviews

ROADMAP(Mind Map) and KEYWORD for students those who have interest in learning NLP

Roadmap to becoming an Artificial Intelligence Expert in 2022

John Hunter Excellence in Plotting Contest

TRPO Implementation in Tensorflow 2.0 for Reinforcement Learning Project @ Sapienza

This function searches (brute search) for the optimal Gray coded map resulting in least PAPR.

This function generates the response time optimal controller parameters for a permanent magnet motor, resulting in zero torque ripple under no measurement noise.

I have implemented the examples presented in David silver's lectures on Ipython notebooks. They can be opened through google colab.

EDA and ML