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Вернуться к Logistic Regression with NumPy and Python

Отзывы учащихся о курсе Logistic Regression with NumPy and Python от партнера Rhyme

Оценки: 68
Рецензии: 10

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....
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1–12 из 12 отзывов о курсе Logistic Regression with NumPy and Python

автор: Chinmay B

May 24, 2020

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

автор: PATIL P R

Apr 04, 2020

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

автор: Mariappan M

May 15, 2020

Clear explanation and good content. Thanks

автор: Pritam B

May 15, 2020

it was an nice experience

автор: Shreyas R

Apr 25, 2020

Amazing. Must do this

автор: Diego R G

May 22, 2020

Great project!

автор: Anisetti S K

Apr 23, 2020

well balanced

автор: Dipak S s

Apr 24, 2020

fine courxe

автор: Mukulesh S

Apr 02, 2020

Problem was that rhyme could not run for more than the alloted time because I had many errors in between because of which I couldn't complete my whole code in the given time.

автор: Girish G A

May 23, 2020

If you are looking for hands on projects after completing Andrew NG Machine Learning Courses, these courses are more of a revision. No explanation about the plots and its parameters. Why it's 0 1 or 2. It would have been nice had there been more explanation about plotting and data visualization. Also accuracy calculated at the end of course seems wrong.

автор: Rick N

Apr 18, 2020

Horrible experience. Learned nothing. Cannot get back to review the material. Locked out? Zero stars.

автор: Sumit M

May 04, 2020

Content is good but explanation is below average.