Product-based-recommendation-system - A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity

Last update: Feb 15, 2022

Overview

Product-based-recommendation-system

A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity and also uses MongoDB as a database which stores the user data for a semi-collaborative filtering.

Accuracy :

Calculated accuracy using nDCG.

Some randomly selected product efficiency:

Batman killer croc takedown figures: nDCG=0.917
Star Wars Movie Heroes Yoda: nDCG=0.942
Harry Potter Hogwarts Bookmarks: nDCG=0.9406

Technology Used in this project:

Pandas
Numpy
Sklearn
MongoDB as Databases
Streamlit for UI

Demo:

Home UI:

Database structure:

Result UI:

Owner

Prem Jha

https://www.kaggle.com/premjha

GitHub Repository

Deep Distributed Control of Port-Hamiltonian Systems

De(e)pendable Distributed Control of Port-Hamiltonian Systems (DeepDisCoPH) This repository is associated to the paper [1] and it contains: The full p

3 Aug 17, 2022

code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"

94 Oct 26, 2022

Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding (CVPR'22) Paper Link | Project Page Abstract : Manual an

152 Dec 23, 2022

MegEngine implementation of YOLOX

Introduction YOLOX is an anchor-free version of YOLO, with a simpler design but better performance! It aims to bridge the gap between research and ind

77 Nov 22, 2022

This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Koltun"

Learning to propose objects This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Ko

90 Sep 10, 2021

Hierarchical Uniform Manifold Approximation and Projection

HUMAP Hierarchical Manifold Approximation and Projection (HUMAP) is a technique based on UMAP for hierarchical non-linear dimensionality reduction. HU

160 Jan 06, 2023

AI grand challenge 2020 Repo (Speech Recognition Track)

KorBERT를 활용한 한국어 텍스트 기반 위협 상황인지(2020 인공지능 그랜드 챌린지) 본 프로젝트는 ETRI에서 제공된 한국어 korBERT 모델을 활용하여 폭력 기반 한국어 텍스트를 분류하는 다양한 분류 모델들을 제공합니다. 본 개발자들이 참여한 2020 인공지

23 Jan 25, 2022

Code for paper ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.

Who Left the Dogs Out? Evaluation and demo code for our ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization

29 Dec 28, 2022

Product-based-recommendation-system - A product based recommendation system which uses Machine learning algorithm such as KNN and cosine similarity

Related tags

Overview

Product-based-recommendation-system

Technology Used in this project:

Demo:

Home UI:

Database structure:

Result UI:

Owner

Prem Jha

最新版本yolov5+deepsort目标检测和追踪，支持5.0版本可训练自己数据集

Deep Distributed Control of Port-Hamiltonian Systems

code for "AttentiveNAS Improving Neural Architecture Search via Attentive Sampling"

Official implementation of "CrossPoint: Self-Supervised Cross-Modal Contrastive Learning for 3D Point Cloud Understanding" (CVPR, 2022)

MegEngine implementation of YOLOX

This implements the learning and inference/proposal algorithm described in "Learning to Propose Objects, Krähenbühl and Koltun"

Hierarchical Uniform Manifold Approximation and Projection

AI grand challenge 2020 Repo (Speech Recognition Track)

Code for paper ECCV 2020 paper: Who Left the Dogs Out? 3D Animal Reconstruction with Expectation Maximization in the Loop.

A project for developing transformer-based models for clinical relation extraction

ICNet for Real-Time Semantic Segmentation on High-Resolution Images, ECCV2018

A tool for calculating distortion parameters in coordination complexes.

Code for T-Few from "Few-Shot Parameter-Efficient Fine-Tuning is Better and Cheaper than In-Context Learning"

Unofficial implement with paper SpeakerGAN: Speaker identification with conditional generative adversarial network

Provide baselines and evaluation metrics of the task: traffic flow prediction

TVNet: Temporal Voting Network for Action Localization

A more easy-to-use implementation of KPConv

Using this codebase as a tool for my own research. Making some modifications to the original repo for my own purposes.

Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems

LibMTL: A PyTorch Library for Multi-Task Learning