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

4.5
380 个评分
48 条评论

课程概述

Welcome to this project-based course on Logistic 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, cost function, and logistic regression, of the various learning algorithms yourself, so you have a deeper understanding of the fundamentals. By the time you complete this project, you will be able to build a logistic regression model using Python and NumPy, conduct basic exploratory data analysis, and implement gradient descent from scratch. The prerequisites for this project are prior programming experience in Python and a basic understanding of machine learning theory. 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

AS
Aug 29, 2020

Very helpful for learning logistic regression without using any libraries. Before taking this project one should have a clear understanding of Logistic Regression, then it will be very helpful

CB
May 23, 2020

Its a good course. Instructor is good. Lot of concepts cleared and enough practice has done.

筛选依据:

1 - Logistic Regression with NumPy and Python 的 25 个评论(共 48 个)

创建者 Sambhaw S

Aug 2, 2020

Excellent course but requires prior theoretical knowledge of logistic regression and linear regression. I have a suggestion for the instructor. If possible, can you attach conceptual videos that are already available on Coursera like liner regression lecture by Andrew Ng or any other lecture, then it will be beneficial for students. Overall a good project for starters like me.

Thank you

创建者 Arnab S

Aug 30, 2020

Very helpful for learning logistic regression without using any libraries. Before taking this project one should have a clear understanding of Logistic Regression, then it will be very helpful

创建者 CHINMAY B

May 24, 2020

Its a good course. Instructor is good. Lot of concepts cleared and enough practice has done.

创建者 MV

Nov 8, 2021

W​ell explained all the basic components of gradient descent. Exactly as advertised.

创建者 Juan M B

Jun 7, 2020

Great tool to practice what i learned in Andrew Yng's ML course about Log. Reg.

创建者 Ramya G R

Jun 9, 2020

I really enjoyed this course. Thank you for your valuable teaching.

创建者 Punam P

Apr 4, 2020

Thank You... Very nice and valuable knowledge provided.

创建者 Thulasi R I 2 B 0

Sep 26, 2020

Able to follow project. Thanks for guiding

创建者 Mari M

May 14, 2020

Clear explanation and good content. Thanks

创建者 Pulkit S

Jun 18, 2020

good project got to learn a lot of things

创建者 Shruti S

Jul 21, 2020

Great course ! very informative

Thanks :)

创建者 Krishna M T

Aug 12, 2020

It is one of the best guided project.

创建者 Melissa d C S

Jun 21, 2020

Please, keep doing good job

创建者 Pulkit D

Oct 16, 2020

good course a lot to learn

创建者 Erick M A

Jul 20, 2020

Excelente aprovechamiento

创建者 Pritam B

May 14, 2020

it was an nice experience

创建者 Shreyas R

Apr 25, 2020

Amazing. Must do this

创建者 Diego R G

May 21, 2020

Great project!

创建者 jagadeeswari N

May 28, 2020

nice overview

创建者 Anisetti S K

Apr 23, 2020

well balanced

创建者 Ayesha N

Jun 16, 2020

its was good

创建者 Dinh-Duy L

Jul 13, 2020

Really good

创建者 Nandivada P E

Jun 15, 2020

Nice course

创建者 Dipak S s

Apr 24, 2020

fine courxe

创建者 Saikat K 1

Sep 8, 2020

Amazing