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banking_customer_segmentation

This project leverages the bank's extensive transactional data collected over the past three years to develop machine learning for segmenting customers based on spending behaviors, facilitating personalized marketing

car-purchasing-customer-classification

The project aims to identify potential Car-repurchasing Customers based on their demographics and historical data.

coding-interview-university

A complete computer science study plan to become a software engineer.

data-science-interview-resources

A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.

deep-high-resolution-net-pytorch

The project is an official implementation of our CVPR2019 paper "Deep High-Resolution Representation Learning for Human Pose Estimation"

deep-person-reid

Torchreid: Deep learning person re-identification in PyTorch.

face-mask-detector

face_recognition_centernet

Using free anchor method to solve Object Detection problem

gitprofile

🚀 Create and deploy a dynamic portfolio by just providing your GitHub username.

hainguyen2903

human_detection_yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

imgcrypt

OCI Image Encryption Package

mercari_price_sugesstion

mmpose_3d_pose_estimation

OpenMMLab Pose Estimation Toolbox and Benchmark.

mot_human_tracking_deepsort

This innovative project seeks to streamline surveillance by efficiently monitoring and tracing the movement of various people using a single camera. The system is a breakthrough step to achieve a more ambitious system, a Muti-Camera Multi-Object Tracking system.

mtmc_annotation_postprocess

no2_estimation

online_face_mask_detector

simple_mnist_wandb_demo

single-shot-detection-pytorch

a lousy reimplementation of single shot detection in pytorch for learning purpose

telecom_customer_understanding

The project aims to gain a comprehensive of customer groups from company's past marketing campaigns to identify new strategy for the upcoming campaign through EDA and ML model development. Customers will then be segmented into different groups to gain deeper insights and optimization strategies.