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Applied Machine Learning in Python に戻る

ミシガン大学(University of Michigan) による Applied Machine Learning in Python の受講者のレビューおよびフィードバック

4.6
6,854件の評価
1,239件のレビュー

コースについて

This course will introduce the learner to applied machine learning, focusing more on the techniques and methods than on the statistics behind these methods. The course will start with a discussion of how machine learning is different than descriptive statistics, and introduce the scikit learn toolkit through a tutorial. The issue of dimensionality of data will be discussed, and the task of clustering data, as well as evaluating those clusters, will be tackled. Supervised approaches for creating predictive models will be described, and learners will be able to apply the scikit learn predictive modelling methods while understanding process issues related to data generalizability (e.g. cross validation, overfitting). The course will end with a look at more advanced techniques, such as building ensembles, and practical limitations of predictive models. By the end of this course, students will be able to identify the difference between a supervised (classification) and unsupervised (clustering) technique, identify which technique they need to apply for a particular dataset and need, engineer features to meet that need, and write python code to carry out an analysis. This course should be taken after Introduction to Data Science in Python and Applied Plotting, Charting & Data Representation in Python and before Applied Text Mining in Python and Applied Social Analysis in Python....

人気のレビュー

OA
2017年9月8日

This course is ideally designed for understanding, which tools you can use to do machine learning tasks in python. However, for deep understanding ML algorithms you should take more math based courses

FL
2017年10月13日

Very well structured course, and very interesting too! Has made me want to pursue a career in machine learning. I originally just wanted to learn to program, without true goal, now I have one thanks!!

フィルター:

Applied Machine Learning in Python: 1176 - 1200 / 1,219 レビュー

by Fernanda T

2020年8月4日

Good content and I learned a lot. However, the instructor made too many mistakes during the lectures and the assignments also have mistakes that need to be fixed by the students.

by Ketan L

2018年6月4日

Follow the course with introduction to ML with python to have descent understanding. Instructor won't be able to keep one interested for long. Exercises could have been tougher.

by Victor E

2017年8月16日

Two point: 1) you can learn a lot here, 2) imagine you are shown a hammer but never explained how to hit a nail. Two previous courses in the specialization do both.

by Kareem H

2020年3月3日

Course instrutor and materials are needed to be improved as they are very poor

Assigments\Quizes are very good and they are the mainly root cause for this rating

by Thomas B

2018年7月7日

Some very good practical advice like dummy testing or data leakage issues Some trivialities and repetitions. Python code could have been a bit better commented

by BIRENDRA H S

2020年6月13日

there should be some low level usage of sentences for a intermediate programmers,most of times it bounces up the mind ,not able to get the required concept

by Baizhu

2017年7月5日

Know some existing machine learning functions and packages from sklearn, but really don't know how to improve prediction accuracy within each function.

by Matteo B

2019年8月10日

Assignments are not really supported by the material provided (videos). The level is not balanced. Some bugs in the assignment code as well

by Berkay A

2020年7月15日

This course seems hard and actually I did not like the syllabus so much. Assignments were so hard and there were some issues in Notebooks.

by Halil K

2019年9月26日

Good content, bad teachng staff. Though the discussion forum contributors were very helpful and should be commended for their efforts.

by Ankur P

2019年3月30日

Unsupervised learning was missing. The codes written in the lectures were not explained clearly. Some topics looked unimportant.

by James F

2018年2月13日

Good overview of methods. A bit too intense at times though, may have been better to really focus on a couple of key concepts.

by Om R

2020年4月26日

The course is great, but need certain improvement for assignments and quizzes. The facts should be checked multiple times.

by Darshan S

2019年12月31日

Not enough real life examples throughout the video, makes it very hard to concentrate during the whole lecture.

by Mauricio A E G M

2019年11月17日

This course is not useful to learn from scratch, but has some good things, for example the final assignment.

by Nikola G

2019年1月14日

Really didn't like the quiz parts of the course. If it was up to me I would do thorough revision of these.

by Chirag S

2020年5月24日

The content was less informative and audio quality was poor. However, assignments are fun completing.

by Rohit S

2020年5月21日

The online grader needs to be updated as there is constant error showing up though our code is right

by Gilad A

2017年6月27日

The last assignment was super. apart for it, the assignments and the course were too easy

by Sai P

2020年6月3日

There were a few corrections made during the videos which ended being quite confusing.

by Philip L

2017年10月31日

The assignments are extremely difficult, professor is a bit dry during lectures.

by Pakin S

2020年1月10日

How can i pass without reading discuss about problem with notebook

by Hao W

2017年8月27日

The homework is too easy to improve our understanding of ML

by M S V V

2020年6月29日

Too much of information compressed within a short span.

by José D A M

2020年6月21日

Too fast, yet too difficult. Needs deeper explanation.