Chevron Left
Вернуться к Applied Machine Learning in Python

Отзывы учащихся о курсе Applied Machine Learning in Python от партнера Мичиганский университет

4.6
звезд
Оценки: 7,130
Рецензии: 1,295

О курсе

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....

Лучшие рецензии

AS
26 нояб. 2020 г.

great experience and learning lots of technique to apply on real world data, and get important and insightful information from raw data. motivated to proceed further in this domain and course as well.

OA
8 сент. 2017 г.

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

Фильтр по:

1101–1125 из 1,273 отзывов о курсе Applied Machine Learning in Python

автор: falak2000

28 окт. 2020 г.

It's really a great course for the beginner to begin with the machine learning basics.

автор: Haldankar S N

29 мая 2020 г.

too much content for 4 weeks course as compared to other courses in the specialization

автор: YJFKD

19 мая 2020 г.

Good course if you want to know how to build machine learning models via scikit-learn.

автор: Sumit t

23 июня 2020 г.

Nice Course and good explanation about practical implementation of machine learning

автор: Niv B

30 июля 2018 г.

On 1x speed, I'd rate it 3 stars, on 1.5x its 4.

The professor just speaks too slow.

автор: Setiadi M

27 июля 2020 г.

This course is good for somebody wanna to know about the Machine Learning, thanks.

автор: tqch

24 июля 2020 г.

Just hoping the problems in assignments/quizzes could be explained more clearly.

автор: Claire-Isabelle C

24 июня 2017 г.

I learned A LOT in this course and was pretty proud to pass all the assignments.

автор: Saori Y

22 июля 2020 г.

The course was really good! However, auto-grading system need to be updated....

автор: SAYANTAN B

9 мая 2020 г.

Very nice and informative course..Keep it up. This course has helped me a lot.

автор: ABHAY T

31 окт. 2020 г.

Please add the explanation on concepts on board.. sure that will impact more!

автор: Hanchi W

18 мая 2019 г.

Good content, some coding assignments are hard to submit(csv file not found)

автор: Vishwanath V

19 дек. 2020 г.

Its well designed course providing good overall concept involved in the ML.

автор: Bharat R

22 авг. 2017 г.

Nice course. Multiple choice quizzes could have been worded a bit better.

автор: Grace Y

15 мая 2020 г.

the material for self-learning after classes is not comprehensive enough.

автор: Douglas P

28 мая 2018 г.

Generally worth while but the automatic grading system could be improved.

автор: Daniel A

1 сент. 2018 г.

Very useful. It's the right course to take after Andrew Ng ML course.

автор: Shwetank A

23 июля 2019 г.

Algorithim are not explained much better, just coding is explained.

автор: Hardik A

4 янв. 2018 г.

An amazing course for learning the application of machine learning.

автор: Tom M

27 сент. 2017 г.

Clean programming examples. A little simplistic for advanced users.

автор: Davide M

24 окт. 2018 г.

Should be an harder final assignement, but a great course overral!

автор: Jeffrey D B

16 окт. 2018 г.

Pretty good class, decent but very quick walk-through of ML tools.

автор: Arun P P

29 июля 2020 г.

It was n insightful course but was quite advanced for a beginner.

автор: Manuela D

8 авг. 2019 г.

Well organised, lots of details, a good overview of ML algorithms

автор: Sang L

28 июля 2018 г.

Speed kinda fast but maganeable. Need more detiailed notes/slides