Md. Muhaimin Rahman's repositories
computer-vision-course
This repo is the homebase of a community driven course on Computer Vision with Neural Networks. Feel free to join us on the Hugging Face discord: hf.co/join/discord
AutonomousDrivingCookbook
Scenarios, tutorials and demos for Autonomous Driving
awesome-bangla
A collection of tools, datasets and resources on Bangla computing
awesome-cloud-robotics
A curated list of awesome resources, tutorials and tools for cloud robotics.
CarND-Catch-Run-Away-Car-UKF
In this Bonus Challenge use an Unscented Kalman Filter to try and catch a car moving in a continuous circle at constant velocity.
CarND-MPC-Quizzes
CarND MPC Quizzes
data-science-interviews
Data science interview questions and answers
fakenews_dataset_ja
Fakenews dataset Japanese
google-research
Google Research
Interactive_Tools
Interactive Tools for Machine Learning, Deep Learning and Math
latexify_py
Generates LaTeX math description from Python functions.
nd013-c1-vision-starter
Starter Code for the Course 1 project of the Udacity Self-Driving Car Engineer Nanodegree Program
nd013-c2-fusion-starter
Starter Code for the Course 2 project of the Udacity Self-Driving Car Engineer Nanodegree Program
NERDA
Framework for fine-tuning pretrained transformers for Named-Entity Recognition (NER) tasks
NeuroNER
Named-entity recognition using neural networks. Easy-to-use and state-of-the-art results.
notebooks
Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
review_object_detection_metrics
Object Detection Metrics. 14 object detection metrics: mean Average Precision (mAP), Average Recall (AR), Spatio-Temporal Tube Average Precision (STT-AP). This project supports different bounding box formats as in COCO, PASCAL, Imagenet, etc.
rl
Release version of my Reinforcement learning study codebase
stable-baselines
A fork of OpenAI Baselines, implementations of reinforcement learning algorithms
tuning_playbook
A playbook for systematically maximizing the performance of deep learning models.