學生對 密歇根大学 提供的 Applied Machine Learning in Python 的評價和反饋

Very good introduction, a lot of information but you feel you are learning the foundations of machine learning.

Excellent course. I'm particularly thankful to the instructor, who was warm-hearted and explained well enough.

A​mazing ocurse focussing on handon application of machine learning alorithms and tools for model evaluation.

This course provides a good introduction to using python in machine learning. It helps me to get hands on it.

Thank you for the very well done course! It's really helpful, has a clear explanation of topics and examples.

Excellent Course each topic is both theoretically as well as as practically explained. Really a good course

Very Intuitive and helpful course for clearing concepts of machine learning and Python's SciKit Learn module

Great Course. Helped me to learn the concepts of Machine Learning and uses of respective Sklearn libraries.

The theoretical part is comprehensive with an excellent balance between the theory and practical exercises.

Excellent collection of various types of Machine Learning Algorithms with visual demonstration and example.

A very good review of important fundamental concepts in Machine Learning focusing on the usage of Sklearn.

This course is Beautifully crafted to cover most of the important concepts of supervised machine learning.

Content and phase are very good. Very clear explanation of topic by the instructor. Appreciate it so much.

The course gives deep knowledge on the subject as well as best practices and strong practice assignments.

the most interesting thing in the course was treating the students as if they are already data scientists

This Course really provides great learning on Advance Machine learning techniques with Python application

Learned a lot in this course! Much better than the previous two and also taught by a different professor.

Taking these lessons from some of the world's most prestigious universities and professors is priceless.

Excellent Course. The only one problem is the duration of videos. The codes in Jupyter are very elegants

What a challenge. Incredible course, no words. Excellent pedagogy from professor Kevyn Collins-Thompson.

Good choice for Machine Learning introduction, Data Analysis in Python and applied statistical concepts.

After this course you will be able to do your own analysis using machine learning which is really great.

Seriously THE BEST for gaining a broad knowledge about machine learning techniques in a applied manner.

A very good course to start journey on data science. Good combination of reading, lecture and practice.

Great course, though was a bit difficult for me, as I wasn't very familiar with math side of the issue