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XG-Boost 101: Used Cars Price Prediction (으)로 돌아가기

Coursera Project Network의 XG-Boost 101: Used Cars Price Prediction 학습자 리뷰 및 피드백

4.6
별점
17개의 평가
5개의 리뷰

강좌 소개

In this hands-on project, we will train 3 Machine Learning algorithms namely Multiple Linear Regression, Random Forest Regression, and XG-Boost to predict used cars prices. This project can be used by car dealerships to predict used car prices and understand the key factors that contribute to used car prices. By the end of this project, you will be able to: - Understand the applications of Artificial Intelligence and Machine Learning techniques in the banking industry - Understand the theory and intuition behind XG-Boost Algorithm - Import key Python libraries, dataset, and perform Exploratory Data Analysis. - Perform data visualization using Seaborn, Plotly and Word Cloud. - Standardize the data and split them into train and test datasets.   - Build, train and evaluate XG-Boost, Random Forest, Decision Tree, and Multiple Linear Regression Models Using Scikit-Learn. - Assess the performance of regression models using various Key Performance Indicators (KPIs). Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

최상위 리뷰

필터링 기준:

XG-Boost 101: Used Cars Price Prediction 의 5개 리뷰 중 1~5

교육 기관: Md. M I C

2021년 3월 18일

Very engaging and clear explanation. One of the best guided projects.

교육 기관: Satya N

2021년 2월 22일

Excellent Course

교육 기관: Gregory G J

2021년 1월 14일

Thumbs Up!

교육 기관: Paúl A A V

2021년 3월 10일

Nice

교육 기관: Akash S C

2021년 5월 29일

Not worth the money! Way short and simple introduction to XGBoost for the price of a full month course on Coursera.