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学生对 Coursera Project Network 提供的 Linear Regression with NumPy and Python 的评价和反馈

4.4
828 个评分
111 条评论

课程概述

Welcome to this project-based course on Linear Regression with NumPy and Python. In this project, you will do all the machine learning without using any of the popular machine learning libraries such as scikit-learn and statsmodels. The aim of this project and is to implement all the machinery, including gradient descent and linear regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, NumPy, and Seaborn pre-installed....

热门审阅

AD
May 24, 2020

It is a great project and an excellent experience to learn practical exposure to Linear regression with nmpy and python. I am waiting to get another project.

VB
Jul 9, 2020

Best Project ever we have seen, all plotting and code are explain in very well manner and its definitely increase my knowledge in machine learning

筛选依据:

76 - Linear Regression with NumPy and Python 的 100 个评论(共 110 个)

创建者 ADITYA V

Jun 13, 2020

It was nice to know how to implement the knowledge I have already gathered. Some prior experience of basic level surely required to understand effectively. Overall worth mine time.

创建者 Abhinandan C

May 12, 2020

Cloud Server was lagging very much. Content was great. Despite of Linear Regression being one of the most basic algorithms, I got to learn quite a few things.

Thank You!

创建者 Yash S

May 31, 2020

I want to give 5 stars but one star is less for rhyme environment it is not good , it's always have some technical problems .I suggest u to use another environment.

创建者 SIVAKUMAR R

May 8, 2020

Fundamentals were clearly made clear. Even though there was a lack of explanations on some areas, the tutor made the topic understandable as a whole.

创建者 ABDULAZIZ A

Nov 1, 2020

Really Good Content, I learnt more however the instructor didn't explain the mathematical expressions of Gradient Descent and matplotlib in details.

创建者 Angela R

May 1, 2020

The server is too slow. One's patience gets tested here. Though these were some cons, the project was apt for learning Linear Regression.

创建者 Anik A

Jun 29, 2020

Good course but make sure to have some previous knowledge of linear algebra especially matrix multiplication.

创建者 Utkarsh S

Jun 12, 2020

Overall it was a good and nice experience if someone wants to practice themselves.

创建者 HARIPRASAD M

Jul 3, 2020

Good Project, but need to make sure more time is available for explanation.

创建者 VISMIT C

Apr 28, 2020

Some parts are well explained and it's pretty easy for a beginner too

创建者 UTKARSH D

Jun 2, 2020

Teachers teaching snkills are very good.Course is good for beginer

创建者 Mohd S B

Apr 18, 2020

I HAVE SLOW CONNECTION IN MY COUNTRY BUT PROJECT IS GOOD

创建者 Divyesh M

Jun 26, 2020

you have to explain more into math equations.

创建者 Khurdula H

May 23, 2020

great course , short and wonderful

创建者 ROHAN K 1

May 1, 2020

good for a foundation.

创建者 Shashank R

Jun 3, 2020

Good One for Starters

创建者 HARSH G

Jun 3, 2020

It was just right

创建者 hemantha k

May 22, 2020

good instucter

创建者 Umesh K P

Jun 7, 2020

Nice Project

创建者 Shashank

May 24, 2020

Basic

创建者 Ashrender K G

Jun 1, 2020

...

创建者 Manav G

Jun 17, 2020

The rhyme was very slow.....and in poor quality...video quality was intermediate but software quality is poor

创建者 Krishno S

Nov 6, 2020

Good. But the python coding could have been explained more. The instructor is knowledgeable and competent

创建者 Mir S H

May 4, 2020

Server was slow. Also for newbies everything is not fully described.

创建者 Mohit M

Apr 27, 2020

Project is awesome but delivered in a boring way.