This comprehensive Supervised and Unsupervised Machine Learning program will equip you with essential skills for data modeling and analysis. You’ll master regression techniques, classification models, and clustering algorithms to address real-world challenges and drive impactful data solutions.
Supervised Learning Regression Classification Clustering
Supervised Learning Regression Classification Clustering
包含在 
中
您将学到什么
Master linear and logistic regression techniques
Apply Decision Trees, Random Forest, and Naive Bayes models
Use K-Means Clustering for data segmentation
Solve real-world problems with machine learning methods
您将获得的技能
要了解的详细信息
可分享的证书
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作业
2 项作业
授课语言：英语（English）
了解顶级公司的员工如何掌握热门技能
积累特定领域的专业知识
本课程是 AI ML with Deep Learning and Supervised Models 专项课程 专项课程的一部分
在注册此课程时，您还会同时注册此专项课程。
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- 获得对主题或工具的基础理解
- 通过实践项目培养工作相关技能
- 获得可共享的职业证书
该课程共有2个模块
This Supervised and Unsupervised Machine Learning program covers essential techniques for data modeling and analysis. Start with regression analysis, mastering linear regression for continuous variable prediction and logistic regression for binary classification. Learn to select the best approach for your projects. Explore classification models, including Decision Trees for data splitting, Random Forest for robust predictions, and Naive Bayes for probabilistic classification. Gain practical skills to apply these methods in real-world scenarios. Dive into unsupervised learning with the K-Means Clustering algorithm, understanding how it groups data into clusters based on similarities. Apply it to challenges like market segmentation and image compression. This program equips you with essential machine learning skills for impactful data solutions.
涵盖的内容
25个视频3篇阅读材料1个作业
Explore clustering techniques, focusing on K-Means, its applications, and real-world use cases.
涵盖的内容
7个视频1篇阅读材料1个作业
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常见问题
Regression predicts continuous outcomes (e.g., sales forecast), classification assigns data into categories (e.g., email spam detection), and clustering groups data based on similarities (e.g., customer segmentation).
A machine learning course can vary in duration, typically lasting from a few weeks for beginner-level programs to several months for comprehensive or advanced courses.
Clustering is an unsupervised learning technique in AI that groups similar data points into clusters, helping to uncover patterns and insights, such as segmenting customers by behavior.
更多问题
提供助学金，