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Linear Regression with NumPy and Python(으)로 돌아가기

Coursera Project Network의 Linear Regression with NumPy and Python 학습자 리뷰 및 피드백

829개의 평가
111개의 리뷰

강좌 소개

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....

최상위 리뷰

2020년 5월 24일

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.

2020년 7월 9일

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

필터링 기준:

Linear Regression with NumPy and Python의 110개 리뷰 중 76~100

교육 기관: ADITYA V

2020년 6월 13일

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.

교육 기관: Abhinandan C

2020년 5월 12일

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!

교육 기관: Yash S

2020년 5월 31일

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.


2020년 5월 8일

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.


2020년 11월 1일

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

교육 기관: Angela R

2020년 5월 1일

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

교육 기관: Anik A

2020년 6월 29일

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

교육 기관: Utkarsh S

2020년 6월 12일

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


2020년 7월 3일

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

교육 기관: VISMIT C

2020년 4월 28일

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

교육 기관: UTKARSH D

2020년 6월 2일

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

교육 기관: Mohd S B

2020년 4월 18일


교육 기관: Divyesh M

2020년 6월 26일

you have to explain more into math equations.

교육 기관: Khurdula H

2020년 5월 23일

great course , short and wonderful

교육 기관: ROHAN K 1

2020년 5월 1일

good for a foundation.

교육 기관: Shashank R

2020년 6월 3일

Good One for Starters

교육 기관: HARSH G

2020년 6월 3일

It was just right

교육 기관: hemantha k

2020년 5월 22일

good instucter

교육 기관: Umesh K P

2020년 6월 7일

Nice Project

교육 기관: Shashank

2020년 5월 24일


교육 기관: Ashrender K G

2020년 6월 1일


교육 기관: Manav G

2020년 6월 17일

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

교육 기관: Krishno S

2020년 11월 6일

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

교육 기관: Mir S H

2020년 5월 4일

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

교육 기관: Mohit M

2020년 4월 27일

Project is awesome but delivered in a boring way.