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Learner Reviews & Feedback for Logistic Regression with NumPy and Python by Coursera Project Network

4.5
stars
391 ratings

About the Course

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 pro...
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Top reviews

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.

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51 - 51 of 51 Reviews for Logistic Regression with NumPy and Python

By Sumit M

May 4, 2020

Content is good but explanation is below average.