Praveen Palanisamy (@praveen-palanisamy)
  • Stars
    star
    1,039
  • Global Rank 29,456 (Top 2 %)
  • Followers 143
  • Following 1
  • Registered over 11 years ago
  • Most used languages
    Python
    41.7 %
    C++
    25.0 %
    HTML
    8.3 %
    PHP
    8.3 %
    TypeScript
    8.3 %
    SCSS
    8.3 %

Top repositories

1

multiple-object-tracking-lidar

C++ implementation to Detect, track and classify multiple objects using LIDAR scans or point cloud
C++
664
star
2

macad-gym

Multi-Agent Connected Autonomous Driving (MACAD) Gym environments for Deep RL. Code for the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
Python
276
star
3

Ape-X-DQN

PyTorch Implementation of Ape-X (Distributed prioritized experience replay) architecture with DQN learner
Python
25
star
4

macad-agents

Agents code for Multi-Agent Connected Autonomous Driving (MACAD) described in the paper presented in the Machine Learning for Autonomous Driving Workshop at NeurIPS 2019:
Python
20
star
5

Robinhood-Insights

A web app to get actionable insights into your Robinhood Portfolio
PHP
9
star
6

Pandaboard-ES

Resources/How-TOs for OMAP4 based Pandaboard ES
C++
8
star
7

webgym

WebGym: Web-browser-based tasks for RL Agents
HTML
8
star
8

OpenCV-2.4.9-for-arm

Prebuilt OpenCV library files for arm v7 cortex-a9 based devices including Pandaboard,I.mx6,ODROID-X
C++
7
star
9

MemReFinder

Finder (File Explorer) App to chat with your Documents and Files powered by LLMs
TypeScript
5
star
10

playwrightgym

PlaywrightGym - Train RL Agents for Web tasks
Python
4
star
11

multi_object_tracking_lidar-release

Release version of multi_object_tracking_lidar ROS package for: Multiple objects detection, tracking and classification from LIDAR scans/point-clouds
3
star
12

openai-retro-contest

Code & experiments done for the transfer learning contest that measures a RL algorithm's ability to generalize from previous experience
Python
1
star
13

praveen-palanisamy.github.io

Praveen Palanisamy's Website/ Blog:
SCSS
1
star