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

4.7
18,298 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

RN

May 25, 2020

Labs were incredibly useful as a practical learning tool which therefore helped in the final assignment! I wouldn't have done well in the final assignment without it together with the lecture videos!

NN

Dec 29, 2019

This is a very good start for Machine leaning with Python. I didnt have much idea about ML concepts but this course gave me great understanding on each topic and lot of learning. Awesome Course !!

筛选依据:

901 - Machine Learning with Python 的 925 个评论(共 3,260 个)

创建者 Moe M

Dec 5, 2024

Amazing course must have for Machine Learning builds very strong foundations

创建者 nikhil r

Apr 3, 2022

Best Course for Beginers and Intermediate level students in Machine Learning

创建者 Ashwini R

Jan 23, 2021

The course thought all the basic key points of ML that I had wanted to learn

创建者 Abu A

Jun 4, 2020

It's a great course with practical and very interesting projects. Thank you!

创建者 Sorrapon M

May 23, 2020

this course is very interesting. lectures and videos are good also the labs.

创建者 Жовтобрюх Д А

Apr 4, 2020

good course to become familiar with the basics of machine learning in python

创建者 Eliana C H L

Mar 17, 2020

Me gustó el curso y los ejercicios, fueron de mucha ayuda. muchas gracias !!

创建者 Shyam P

Feb 18, 2020

I recommend this course for anyone to head start a machine learning venture.

创建者 Yash J

Jan 20, 2020

Wonderful course. One must do it to enhance their career in Machine learning

创建者 Himanshu P

Jan 3, 2020

A brief revision or description of numpy and pandas function should be given

创建者 Carlos F S

Apr 2, 2019

TOP! V ery useful and impressed how difficult topics are explained so easy!!

创建者 Chánh T T

Jul 24, 2022

Thank you so much. This is such a nice course. I learned so much from this.

创建者 Brian B J

Mar 24, 2022

Fine course for getting the basics of machine learning with python covered.

创建者 Duarte

Mar 15, 2022

A nice course for an introduction to the main machine learning techniques.

创建者 Erich H

Sep 21, 2021

Love the hands on and the work on the data set with different ML techinques

创建者 Romil N

May 23, 2020

great assignments for practice..great course for machine learning in python

创建者 Ishraque Z B

Apr 28, 2020

An Excellent and easy way to understand critical concept. Highly recommend.

创建者 Rida Z

Apr 4, 2020

Amazing course, I got only gained theroritical but also technical knowledge

创建者 Santhosh R

Jan 3, 2020

The lab exercises are very good. The pace of the course will suit everyone.

创建者 Christopher C

Sep 18, 2019

Excellent course. Peer review quality for final project was extremely poor.

创建者 Krishna P G

Oct 16, 2025

Gave me a detailed intro to ML when I was clueless about what why and when

创建者 Jitendra B 2

Apr 12, 2025

Absolutely fantastic course and I've learned from scratch from this course

创建者 Muhammad M

Jul 24, 2023

Too helpful and easy to understand different concepts of machine learning.

创建者 Bui N H T

Aug 23, 2021

Excellent course but I would like to learn more in classification problems

创建者 Jesús V

Aug 17, 2021

Great starting course for anyone interested in the Machine Learning field.