Pinned Repositories
A2C-Exploring-OpenAI-Gym-Environments-and-Enhancing-Actor-Critic-Algorithms-for-Optimal-Performance
This project provides a comprehensive understanding of reinforcement learning, focusing on Actor Critic Algorithms. It involves exploring the OpenAI Gym library, implementing the A2C algorithm from DeepMind's seminal paper, and enhancing the A2C algorithm for improved performance and stability.
Adaptive-Deep-Learning-for-Environment-Agnostic-Human-Action-Recognition
This repository dedicated to Adaptive Deep Learning for Environment-Agnostic Human Action Recognition. This project focuses on developing a robust deep learning system tailored for accurate identification and analysis of human actions across diverse environments, with applications spanning surveillance, security, sports, and fitness.
CodeName-Detective
My GitHub Portfolio
CUDA_GPGPUs_Shared_Memory_Systems_PDP
CUDA GPGPUs Shared Memory Systems Parallel & Distributed Programming
Data_Mining
Projects Related To Data Mining
Deep-Q-Learning-Exploring-OpenAI-Gym-Environments-and-Enhancing-DQN-for-Optimal-Performance
This project provides a comprehensive understanding of reinforcement learning, focusing on Deep Q-Learning (DQN). It involves exploring the OpenAI Gym library, implementing DQN from DeepMind's seminal paper, and enhancing the DQN algorithm for improved performance and stability.
First_Principles_Of_Computer_Vision
Multiple Projects Related To First Principles of Computer Vision
Multi-Agent-RL-in-Gridworld-Complex-Environments
MARL explores cooperation & competition in gridworlds. Batman & Robin team up (DQN, CQL, MAD-DQN, REINFORCE). Adversaries use MADDPG with CLDE for strategy.
Prompt-to-Song-Generation-using-Large-Language-Models
This project uses LLMs to generate music from text by understanding prompts, creating lyrics, determining genre, and composing melodies. It harnesses LLM capabilities to create songs based on text inputs through a multi-step approach.
Self_Driving_Cars_Fundamentals
Hands-on implementations of fundamental self-driving car concepts: stereo depth, LiDAR plane fitting, occupancy grid mapping, Extended Kalman Filter, vehicle models, mission planning, and parameter estimation.
CodeName-Detective's Repositories
CodeName-Detective/Prompt-to-Song-Generation-using-Large-Language-Models
This project uses LLMs to generate music from text by understanding prompts, creating lyrics, determining genre, and composing melodies. It harnesses LLM capabilities to create songs based on text inputs through a multi-step approach.
CodeName-Detective/Multi-Agent-RL-in-Gridworld-Complex-Environments
MARL explores cooperation & competition in gridworlds. Batman & Robin team up (DQN, CQL, MAD-DQN, REINFORCE). Adversaries use MADDPG with CLDE for strategy.
CodeName-Detective/Adaptive-Deep-Learning-for-Environment-Agnostic-Human-Action-Recognition
This repository dedicated to Adaptive Deep Learning for Environment-Agnostic Human Action Recognition. This project focuses on developing a robust deep learning system tailored for accurate identification and analysis of human actions across diverse environments, with applications spanning surveillance, security, sports, and fitness.
CodeName-Detective/Self_Driving_Cars_Fundamentals
Hands-on implementations of fundamental self-driving car concepts: stereo depth, LiDAR plane fitting, occupancy grid mapping, Extended Kalman Filter, vehicle models, mission planning, and parameter estimation.
CodeName-Detective/A2C-Exploring-OpenAI-Gym-Environments-and-Enhancing-Actor-Critic-Algorithms-for-Optimal-Performance
This project provides a comprehensive understanding of reinforcement learning, focusing on Actor Critic Algorithms. It involves exploring the OpenAI Gym library, implementing the A2C algorithm from DeepMind's seminal paper, and enhancing the A2C algorithm for improved performance and stability.
CodeName-Detective/CodeName-Detective
My GitHub Portfolio
CodeName-Detective/CUDA_GPGPUs_Shared_Memory_Systems_PDP
CUDA GPGPUs Shared Memory Systems Parallel & Distributed Programming
CodeName-Detective/Data_Mining
Projects Related To Data Mining
CodeName-Detective/Deep-Q-Learning-Exploring-OpenAI-Gym-Environments-and-Enhancing-DQN-for-Optimal-Performance
This project provides a comprehensive understanding of reinforcement learning, focusing on Deep Q-Learning (DQN). It involves exploring the OpenAI Gym library, implementing DQN from DeepMind's seminal paper, and enhancing the DQN algorithm for improved performance and stability.
CodeName-Detective/First_Principles_Of_Computer_Vision
Multiple Projects Related To First Principles of Computer Vision
CodeName-Detective/Inverted-Index-DAAT-Python-Flask
This repository hosts a Python-based project that implements an advanced Inverted Index using a Linked List structure, and Boolean Retrieval. It leverages Flask to create a web application that allows users to perform Boolean queries through a Document-at-a-time (DAAT) strategy. Optimized for fast retrieval and efficient storage.
CodeName-Detective/MPI_Hybrid_Distributed_Memory_Systems_NUMA_PDP
Parallel Algorithms for Distributed Memory Hybrid systems using MPI.
CodeName-Detective/Neural-Image-Classification
Neural Image Classification repository, where cutting-edge deep learning models have been crafted and fine-tuned for diverse image classification tasks. Leveraging state-of-the-art architectures and innovative techniques, this repository stands as a testament to high-performance image recognition.
CodeName-Detective/Neural-Machine-Translation
This GitHub repository houses an innovative implementation of Neural Machine Translation (NMT) using state-of-the-art sequence-to-sequence networks. The primary focus is on enhancing translation quality through progressively advanced architectural improvements.
CodeName-Detective/NovelConvo-AI-Intelligent-Conversations-with-Literary-Companions
NovelConvo AI engages users in dynamic conversations about curated novels. With chit-chat and Q/A components, it's a literary companion delivering both entertainment and information. An immersive AI experience for novel enthusiasts.
CodeName-Detective/Linear_Algebra_And_Numerical_Optimization
This repository provides implementations of various algorithms in linear algebra and numerical optimization.
CodeName-Detective/OpenMP_Shared_Memory_Systems_NUMA_PDP
Parallel Algorithms for Shared Memory systems using OpenMP.
CodeName-Detective/Reinforcement-Learning-for-Stock-Market-Trading-A-Case-Study-on-Nvidia-Stock
This project applies a Q-learning agent to develop a trading strategy that maximizes profit through stock trading. The environment is based on historical stock prices of Nvidia over the past two years, containing 504 entries from 02/01/2021 to 01/31/2023.
CodeName-Detective/Robust-Pathfinding-Tabular-and-DeepRL-in-Deterministic-and-Stochastic-Grid-Worlds
This project explores robust pathfinding solutions using both tabular and deep reinforcement learning techniques in various grid world environments. The environments include deterministic and stochastic settings, each with unique reward structures and transition dynamics.
CodeName-Detective/ROS_Projects
CodeName-Detective/Self_Driving_Cars_Control
🧠2D Longitudinal and Lateral Controller for CARLA simulator. Implements a PID-based throttle/brake system and a Stanley steering controller for waypoint-following autonomous vehicle navigation.
CodeName-Detective/Self_Driving_Cars_Environment_Perception
This project focuses on key perception tasks for self-driving cars, including ground plane estimation from 3D data, semantic segmentation to identify drivable areas, and detection of lanes and obstacles. By combining these techniques, the system helps autonomous vehicles understand their environment for safe and efficient navigation.
CodeName-Detective/Self_Driving_Cars_State_Estimation_and_Localization
Real-time vehicle state estimation using Error-State Extended Kalman Filter (ES-EKF) with IMU, GNSS, and LIDAR data. Includes sensor fusion, trajectory visualization, and error analysis.
CodeName-Detective/Self_Driving_Cars_Visual_Odometry
This repository implements monocular visual odometry using feature matching and essential matrix–based motion estimation. It recovers camera trajectory from image sequences using 2D-2D correspondences and supports trajectory reconstruction with optional homogeneous transformations.