李宏毅机器学习课程作业—2021

The Used Car Price Prediction project aims to develop a robust data science solution for accurately predicting used car prices. Leveraging a diverse dataset encompassing essential features like car model, number of owners, age, mileage, fuel type, kilometers driven, additional features, and location, this project aspires to build a powerful machine

The "Industrial Copper Modeling" project is designed to enhance your proficiency in data analysis and machine learning, focusing on the challenges posed by complex sales and pricing data in the copper industry. This hands-on project employs advanced machine learning techniques to provide solutions, offering regression models for precise pricing pre

Image Classification in TensorFlow (Submission Dicoding Indonesia) - Kelas Belajar Machine Learning untuk Pemula

Projekt transformacja, czyli Matrix - poznaj reguły gry

learning notes of the book Statistical learning methods, 统计学习方法[李航] [笔记, 代码, notebook, lihang]

기계학습 대체과제 c++로 제출하기 프로젝트. 학점은 보장 못함;;

A dataset containing 1300 Iranian IT job advertisements in English from August 2019 to January 2021 and collected by using a new crowdsourcing-based dataset gathering process.

Malware detection project by Machine Learning Algorithms. Top class BE second year project of EnTC students . It detects and tells the accuracy through Machine Learning Algorithms.

this can be done by open-cv

ML Loan Approvel Prediction using Python

Contributed to the improvement of risk management practices in the lending industry. Led to more responsible lending practices and reduced financial risks

Classification Using Frequent Patterns - UEH

Learning repository for ML

Anomaly detection algorithm related papers, competition schemes, codes, etc

HeaithCare Diabetics Machine Learning model Deployment by using Flask app.

In the real estate industry, the determination of rental prices plays a critical role in shaping the interactions between property owners, tenants, and property management companies. The ever-changing nature of the real estate market necessitates a dynamic and data-driven approach to set competitive and fair rental prices.