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Вернуться к Logistic Regression with NumPy and Python

Отзывы учащихся о курсе Logistic Regression with NumPy and Python от партнера Coursera Project Network

4.5
звезд
Оценки: 372
Рецензии: 46

О курсе

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....

Лучшие рецензии

AS
29 авг. 2020 г.

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
23 мая 2020 г.

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

Фильтр по:

1–25 из 46 отзывов о курсе Logistic Regression with NumPy and Python

автор: Sambhaw S

2 авг. 2020 г.

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

автор: Arnab S

30 авг. 2020 г.

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

автор: CHINMAY B

24 мая 2020 г.

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

автор: Juan M B

7 июня 2020 г.

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

автор: Ramya G R

9 июня 2020 г.

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

автор: Punam P

4 апр. 2020 г.

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

автор: Thulasi R I 2 B 0

26 сент. 2020 г.

Able to follow project. Thanks for guiding

автор: Mariappan M

14 мая 2020 г.

Clear explanation and good content. Thanks

автор: Pulkit S

18 июня 2020 г.

good project got to learn a lot of things

автор: Shruti S

21 июля 2020 г.

Great course ! very informative

Thanks :)

автор: Krishna M T

12 авг. 2020 г.

It is one of the best guided project.

автор: Melissa d C S

21 июня 2020 г.

Please, keep doing good job

автор: Pulkit D

16 окт. 2020 г.

good course a lot to learn

автор: Erick M A

20 июля 2020 г.

Excelente aprovechamiento

автор: Pritam B

14 мая 2020 г.

it was an nice experience

автор: Shreyas R

25 апр. 2020 г.

Amazing. Must do this

автор: Diego R G

21 мая 2020 г.

Great project!

автор: jagadeeswari N

28 мая 2020 г.

nice overview

автор: Anisetti S K

23 апр. 2020 г.

well balanced

автор: Ayesha N

16 июня 2020 г.

its was good

автор: Duy L Đ

13 июля 2020 г.

Really good

автор: Nandivada P E

15 июня 2020 г.

Nice course

автор: Dipak S s

24 апр. 2020 г.

fine courxe

автор: Saikat K 1

8 сент. 2020 г.

Amazing

автор: Dibyanshu S D

13 авг. 2020 г.

Great