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

wonderful course. It requires a lot of self learning time to be honest. For my case, I have to do a lot of google search and background reading so to keep up to the learning pace of this mooc. However, I am very happy to be able to finish the assignments and it feels productive.

Helped me to get the solid concept of Machine Learning. Since this course is mainly focused on the ways to use the machine learning skills in the real world problems, if you are interested in the mathematical approach of each skill, you might need to look into the other courses.

Consider about buying this course if you have some pre-knowledge about ML....Understand that this is not a full ML Course, but a course that describes a lot about applications of this and different ML Algorithms. But this a very good course cause it does what it says very well.

I really like that this course focuses on the application of machine learning methods, at the same time still provide enough insight of the working of each model. I do have the math background to follow the proofs, but I would rather spend my time doing rather than proofing.

The course was very useful, however, few of the assignments (specifically assignment 2) had a few errors in accurately displaying the question content and grading method was found to be slightly inconsistent with what was asked in the cells (Jupyter notebook).

4.5/5.0 stars

One of the best courses I have taken online! The professor lectures are great and very well laid out. The assignments are very challenging and meant to teach you real life scenarios. Highly recommend to anyone who wants to learn the basics of machine learning using Python.

Excellent course. Not only show how to use python for machine learning, it also teaches the key points in order to achieve a good model. Highly recommended, The instructor provides a clear message about the general idea of machine learning and the most important aspects.

This course is my first machine learning course. The instructor was very much helpful. Thank you Coursera and University of Michigan for providing this course online to help thousands of machine learning beginners to pave the way of advanced machine learning. Thank you.

Really really good introduction to applied machine learning. It resolves the fear from the difficult application of complex mathematical formulas. It demystifies the topic of machine learning and provides a perfect introduction how to approach real world problems.

One of the best courses I have ever taken. I wish I would have taken this course earlier. it gives provides you with a lot of practical tools in a shortest time. This course is perfectly designed and the instructor conveys information in the most efficient way.

Following the first 2 sessions of this specialisation, this one seems easy and gives the student a lot of confidence. Make sure you follow the sequence suggested in this specialization, even if you do not plan to continue with Text Mining and Social Networks.

Challenging but worthwhile mix of essential theory (explained well) and hand-on practice with good, sensible exercises to help one get a confident grasp of scikit learn packages which one can use in the real world. Many thanks to the organisers and Coursera.

The Instructor is marvelous. The Assignments are amazing, The TA is really responsive. The content only for one month course was outstanding, my feedback would be to increase the amount of exercises(coding) and assignments, and make the course for 2 months.

Excellent introduction into machine learning with Python. I came into this class with little knowledge of machine learning and was taking this to aid in my data science career. As a result of this course, I've decided to focus more on machine learning.

This course does a really good job taking you through the basics of ML through use of Scikit Learn models. It goes over a broad swath of models in a black-box fashion so you can start getting a feel for how each model is tuned and what parameters to use.

Assignments and quizzes help you a lot in consolidating the concepts. However, some questions in quizzes are tricky but not in a way that really adds to your understanding of the topic. Overall a pretty good course. (4.5/5 is the rating I would give)

This course is well-structured and I learned a lot from it. Students who use retrieval practice, which is a form of self-testing, retain the information longer and learn better. I liked the quizzes and the assignments, and I wished there were more.

The course content is excellent and the instructor makes stuffs easier. Few assignments are very tough but if you go through the course properly can able to solve it. One request to the instructors to a bit slow the pace for better understanding. :)

Though it just give us a limited amount of information about Machine Learning, it really drive me into the novel world of this field.The course told me a lot of basic concepts about ML, thus I can go through many thesis related to the realm, thanks.

Very practical lectures for implementing machine learning. Provides more hands on experience and you can get familiar with python machine learning libraries with this course. Highly recommend if you want to really practice machine learning coding.

The course ire great and illustrates many useful topics. The only thing it needs to improve is about the assignment 4 which requires more information to solve the problem, in particular, people who deal with the complete machine learning problem.

The programming assignments where though because the automatic grader was very picky. Please change it so it gives the user more input about what part of their code is wrong. Also Have a repository where the user can retrieve previous submissions.

Excellent course !!!!! very useful for people who have just completed python and wanted to apply the language. Much more clear when we do the course after studying the libraries of python , very clear explanation throughout the entire course .

It was a great learning experience. The way the course structure is curated is truly adapting to the current trends in field of ML and AI. Thank you for giving me an opportunity to learn from best teachers on a great online learning platform.

Fantastic course theory and material. Additional vague pointers would have been useful for Assignment 4 to help understand required data manipulation not included in the notebooks.

Many thanks to the team and Professor Kevyn Collins-Thompson