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Logistic Regression with NumPy and Python(으)로 돌아가기

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

4.5
별점
379개의 평가
47개의 리뷰

강좌 소개

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....

최상위 리뷰

AS
2020년 8월 29일

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
2020년 5월 23일

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

필터링 기준:

Logistic Regression with NumPy and Python의 47개 리뷰 중 1~25

교육 기관: Sambhaw S

2020년 8월 2일

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

교육 기관: Arnab S

2020년 8월 30일

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

교육 기관: CHINMAY B

2020년 5월 24일

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

교육 기관: Juan M B

2020년 6월 7일

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

교육 기관: Ramya G R

2020년 6월 9일

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

교육 기관: Punam P

2020년 4월 4일

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

교육 기관: Thulasi R I 2 B 0

2020년 9월 26일

Able to follow project. Thanks for guiding

교육 기관: Mari M

2020년 5월 14일

Clear explanation and good content. Thanks

교육 기관: Pulkit S

2020년 6월 18일

good project got to learn a lot of things

교육 기관: Shruti S

2020년 7월 21일

Great course ! very informative

Thanks :)

교육 기관: Krishna M T

2020년 8월 12일

It is one of the best guided project.

교육 기관: Melissa d C S

2020년 6월 21일

Please, keep doing good job

교육 기관: Pulkit D

2020년 10월 16일

good course a lot to learn

교육 기관: Erick M A

2020년 7월 20일

Excelente aprovechamiento

교육 기관: Pritam B

2020년 5월 14일

it was an nice experience

교육 기관: Shreyas R

2020년 4월 25일

Amazing. Must do this

교육 기관: Diego R G

2020년 5월 21일

Great project!

교육 기관: jagadeeswari N

2020년 5월 28일

nice overview

교육 기관: Anisetti S K

2020년 4월 23일

well balanced

교육 기관: Ayesha N

2020년 6월 16일

its was good

교육 기관: Dinh-Duy L

2020년 7월 13일

Really good

교육 기관: Nandivada P E

2020년 6월 15일

Nice course

교육 기관: Dipak S s

2020년 4월 24일

fine courxe

교육 기관: Saikat K 1

2020년 9월 8일

Amazing

교육 기관: Dibyanshu S D

2020년 8월 13일

Great