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Avis et commentaires pour d'étudiants pour Logistic Regression with NumPy and Python par Coursera Project Network

4.5
étoiles
269 évaluations
35 avis

À propos du cours

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....

Meilleurs avis

CB

May 24, 2020

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

RR

Jun 09, 2020

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

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1 - 25 sur 36 Avis pour Logistic Regression with NumPy and Python

par Sambhaw S

Aug 02, 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

par Chinmay B

May 24, 2020

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

par Juan M B

Jun 07, 2020

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

par Ramya G R

Jun 09, 2020

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

par Punam P

Apr 04, 2020

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

par Mariappan M

May 15, 2020

Clear explanation and good content. Thanks

par Pulkit S

Jun 18, 2020

good project got to learn a lot of things

par Shruti S

Jul 21, 2020

Great course ! very informative

Thanks :)

par Krishna M T

Aug 12, 2020

It is one of the best guided project.

par Melissa d C S

Jun 22, 2020

Please, keep doing good job

par Erick M A

Jul 20, 2020

Excelente aprovechamiento

par Pritam B

May 15, 2020

it was an nice experience

par Shreyas R

Apr 25, 2020

Amazing. Must do this

par Diego R G

May 22, 2020

Great project!

par jagadeeswari N

May 29, 2020

nice overview

par Anisetti S K

Apr 23, 2020

well balanced

par Ayesha N

Jun 16, 2020

its was good

par Duy L Đ

Jul 13, 2020

Really good

par Nandivada P E

Jun 15, 2020

Nice course

par Dipak S s

Apr 24, 2020

fine courxe

par PRAVEEN K K S

Jul 06, 2020

NIICE

par p s

Jun 12, 2020

Super

par Yurii S

Jun 09, 2020

GREAT

par tale p

Jun 26, 2020

good

par Yogesh P

Jun 14, 2020

I have just started learning machine learning and I found out that, to brush up my foundational skills, this project was just the right one for me. The explanations are spot on and the learning experience was also quite fruitful. Highly recommended.