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学生对 IBM 提供的 Machine Learning with Python 的评价和反馈

4.7
17,995 个评分

课程概述

Python is a core skill in machine learning, and this course equips you with the tools to apply it effectively. You’ll learn key ML concepts, build models with scikit-learn, and gain hands-on experience using Jupyter Notebooks. Start with regression techniques like linear, multiple linear, polynomial, and logistic regression. Then move into supervised models such as decision trees, K-Nearest Neighbors, and support vector machines. You’ll also explore unsupervised learning, including clustering methods and dimensionality reduction with PCA, t-SNE, and UMAP. Through real-world labs, you’ll practice model evaluation, cross-validation, regularization, and pipeline optimization. A final project on rainfall prediction and a course-wide exam will help you apply and reinforce your skills. Enroll now to start building machine learning models with confidence using Python....

热门审阅

FO

Oct 8, 2020

I'm extremely excited with what I have learnt so far. As a newbie in Machine Learning, the exposure gained will serve as the much needed foundation to delve into its application to real life problems.

RC

Feb 6, 2019

The course was highly informative and very well presented. It was very easier to follow. Many complicated concepts were clearly explained. It improved my confidence with respect to programming skills.

筛选依据:

2626 - Machine Learning with Python 的 2650 个评论(共 3,224 个)

创建者 Thanh K ( V

Apr 26, 2020

most of the codes are too hard to follow, need more detail narrations

创建者 Dorjee G

Nov 11, 2019

Great course, great instructor. I enjoyed doing the Lab works.

Thanks,

创建者 Mahendra S

Jul 21, 2019

Contents are very useful and informative. A good start for beginners.

创建者 Yusuf A Y

Jul 25, 2025

I really appreciated the structure and clarity of the whole course.

创建者 Mujeebullah Y

Oct 23, 2019

Good course. However, they need to explain the code more in details.

创建者 Subhara S

Oct 26, 2022

This was a very good course who are want to learn the basics from.

创建者 Danny R

Jan 30, 2024

Decent theoretical intro to machine learning but not much practice

创建者 Alexandre N

Dec 21, 2020

Recommendation systems could receive a peer-reviewed task as well.

创建者 Hemanth A

Jul 6, 2020

A good platform for users curious about the various ML techniques.

创建者 Dhruv V C

May 10, 2020

Marks were deducted for no reason in the peer graded assignment .

创建者 Alexios M

Mar 13, 2021

Well-structured course. It drives you stop-by-step in most cases.

创建者 Harish K

Jun 30, 2023

This course is very useful and also helps to improve your skills

创建者 Nitai S

Dec 7, 2021

notebook setups for final projects could have been much better.

创建者 mohd z

Jun 22, 2021

Awesome course with excellent content and Project based learning

创建者 Ayushman S

Apr 6, 2020

Some concepts were hurried. But jypyter notebooks are very good.

创建者 Felicia C

Dec 7, 2024

overall good, but I'd prefer more coding practice in python lab

创建者 Abhinav K

Mar 2, 2019

A complete package for those who want to start from the stratch

创建者 Tao W

Dec 31, 2023

- well structured content - I like jupyter lab, fun to try out

创建者 Tien C B

Jan 4, 2023

There are a few misleading and vague questions in the content.

创建者 Amlan G

Jul 21, 2022

This is a very gd course for a student to learn ML with python

创建者 Subash L

Jun 26, 2021

Over all good. The lab results could be explained a bit better

创建者 KOSHAL K

Feb 10, 2020

It is best for beginners for introduction to machine learning.

创建者 Prakash R

Feb 10, 2019

This course helps me to get understand about Machine Learning.

创建者 Rajesh K

Mar 20, 2025

very good course,but it still feels like course taught by AI.

创建者 Mohamed K

Nov 19, 2024

pythopn coding execices should be graded at my point of view