Hello everyone and welcome to this new hands-on project on Scikit-Learn for solving machine learning regression problems. In this project, we will learn how to build and train regression models using Scikit-Learn library. Scikit-learn is a free machine learning library developed for python. Scikit-learn offers several algorithms for classification, regression, and clustering. Several famous machine learning models are included such as support vector machines, random forests, gradient boosting, and k-means.

Scikit-Learn to Solve Regression Machine Learning Problems

位教师:Ryan Ahmed
访问权限由 Coursera Learning Team 提供
1,628 人已注册
您将学到什么
Train machine learning regression models using Scikit-Learn library
Understand the theory and intuition behind XG-Boost regression model
Evaluate several trained regression models performance using various Key Performance Indicators (KPIs)
您将练习的技能
要了解的详细信息

添加到您的领英档案
仅桌面可用
了解顶级公司的员工如何掌握热门技能

在 2 小时内学习、练习并应用岗位必备技能
- 接受行业专家的培训
- 获得解决实训工作任务的实践经验
- 使用最新的工具和技术来建立信心

关于此指导项目
分步进行学习
在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:
-
Understand the Problem Statement
-
Import Key Libraries and Datasets
-
Practice Opportunity #1 [Optional]
-
Perform Data Visualization
-
Perform Feature Engineering
-
Understand XG-Boost Algorithm
-
Train an XG-Boost Regression Model
-
Evaluate Trained Model Performance
-
Practice Opportunity #2 [Optional]
-
Final Capstone Project
推荐体验
Python programming and Machine Learning Basics
10个项目图片
位教师

提供方
学习方式
基于技能的实践学习
通过完成与工作相关的任务来练习新技能。
专家指导
使用独特的并排界面,按照预先录制的专家视频操作。
无需下载或安装
在预配置的云工作空间中访问所需的工具和资源。
仅在台式计算机上可用
此指导项目专为具有可靠互联网连接的笔记本电脑或台式计算机而设计,而不是移动设备。
人们为什么选择 Coursera 来帮助自己实现职业发展

Felipe M.

Jennifer J.

Larry W.






