Ratings and Reviews for Applied Machine Learning in Python

I do not have the impression after this course that I have reached a level of familiarity that I will continue using the content of this course. Disappointing.

From this course you will learn direct application of Machine Learning using python. You can dive into the world of machine learning. Ipython notebooks used are really helpful. Learned a lot from this course.

Very good, comprehensive course!

Really challenging course!

Great course, with a very practical overview of the different options available for machine learning models using Python. The concepts are the same as in R-based machine learning, but this course was great for getting experience with which Python functions to use for various machine learning models.

This course is an survey on how to implement many machine learning techniques using the SciKit Learn library. Following the course, you can learn several interesting details about how to work in the field, but it is important to take into account that it is not possible to learn the algorithms during the course, since a huge amount of material is covered during a short time; to make the most of the course you have to know them in advance. It bothered me to discover that the course was planned for five weeks but Coursera has reduced it to four, removing the possibility of practicing exercises on unsupervised learning.

Excellent introductory course to machine learning using python. It covers the basics for the popular supervised machine learning algorithms. I'm excited to build on the knowledge this course has given me.

Good course. Thanks to entire team Harsh Arora.

Excellent course! Well paced lectures, challenging quiz questions that also require insight and understanding, and programming assignments with explicit instructions leading to very little auto grader frustration. The perfect python complement to Andrew Ngs machine learning course.

It is helpful for me to be familiar with scikit-learn