返回到 Exploratory Data Analysis for Machine Learning
学生对 IBM 提供的 Exploratory Data Analysis for Machine Learning 的评价和反馈
2,477 个评分
课程概述
This first course in the IBM Machine Learning Professional Certificate introduces you to Machine Learning and the content of the professional certificate. In this course you will realize the importance of good, quality data. You will learn common techniques to retrieve your data, clean it, apply feature engineering, and have it ready for preliminary analysis and hypothesis testing.
By the end of this course you should be able to:
Retrieve data from multiple data sources: SQL, NoSQL databases, APIs, Cloud
Describe and use common feature selection and feature engineering techniques
Handle categorical and ordinal features, as well as missing values
Use a variety of techniques for detecting and dealing with outliers
Articulate why feature scaling is important and use a variety of scaling techniques
Who should take this course?
This course targets aspiring data scientists interested in acquiring hands-on experience with Machine Learning and Artificial Intelligence in a business setting.
What skills should you have?
To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Calculus, Linear Algebra, Probability, and Statistics.
热门审阅
ML
Sep 21, 2021
Excellent, very detailed. However, if the lessons can be expand for hypothesis testing and some of their common test like T test, Anova 1 and 2 way, chi square,..it would be better further.
BD
Apr 23, 2024
The course includes hands-on exercises that allows us to apply the learned EDA techniques to real-world data. This practical approach helps solidify my understanding.
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501 - Exploratory Data Analysis for Machine Learning 的 502 个评论（共 502 个）
创建者 MARILIA F
•Aug 4, 2023
ainda não entendi o que é machine learning
创建者 Lawrence P
•May 6, 2024
need case studies