jahidmunna Goto Github PK

job_searching

searching job and get the link using simple python script

jupyter-notebook-server

make a server for jupyter notebook

kali_linux

Kali linux on docker

labelme

Image Polygonal Annotation with Python (polygon, rectangle, circle, line, point and image-level flag annotation).

learn_git

learning git

leetcode

solving leet code problem

llama-2-open-source-llm-cpu-inference

Running Llama 2 and other Open-Source LLMs on CPU Inference Locally for Document Q&A

llms

Testing By Own

machine_learning

machine_learning_a-z

Repository contains tasks and exercises made during Udemy course Machine Learning A-Z that I completed in 2017.

malware_showcase

Understand the nature of malicious software with practical examples in Python.

mlx

MLX: An array framework for Apple silicon

mmsegmentation

OpenMMLab Semantic Segmentation Toolbox and Benchmark.

modnet

A Trimap-Free Solution for Portrait Matting in Real Time under Changing Scenes

my-app

notebooks_cv

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.

np_pt_dl

Numpy, PyTorch, DeepLearning -> Basics

personal-website-streamlit

purera

Water Jar Supply Management System

python

pytorch-image-models

PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more

pytorch-nested-unet

PyTorch implementation of UNet++ (Nested U-Net).

pytorch_examples

pyvis_graph

For Generating Graph

qr_code_generator

realtimewaterqualitymonitor

Real-time Water Quality Monitoring Web Version

research-papers

sample_flask

scalabeginnerudemy

Language Only

segment-anything

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.