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Вернуться к Applied Machine Learning in Python

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

4.6
звезд
Оценки: 7,252
Рецензии: 1,319

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.

FL
13 окт. 2017 г.

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!!

Фильтр по:

1276–1296 из 1,296 отзывов о курсе Applied Machine Learning in Python

автор: Shan J

12 апр. 2020 г.

The explanation could have been much better.

автор: Sagar J

21 мар. 2021 г.

Good start but i was very boring later on.

автор: Jeremy D

10 июля 2017 г.

The topics were good, but too many were d

автор: Ryan S

12 дек. 2017 г.

Homeworks are inconvenient to submit

автор: PIYUSH A

16 мая 2020 г.

The narration was a bit boring.

автор: shreyas

29 июня 2020 г.

Teacher wasn't very good

автор: Abir H R

30 июня 2020 г.

very long videos

автор: Wojciech G

28 окт. 2017 г.

To fast paced.

автор: Aarya P

30 сент. 2020 г.

Really disappointed with the course ...you may ask why??

The first thing is the instructor , super boring. The instructor (with all due respect) was very dry and the lectures were super uninteresting. When he keeps on talking code, but doesn't really explain stuff. The material and lectures were dry and colorless.

Me without having good statistics background had huge difficulties understanding the concepts. Please i recommend everyone to have good knowledge in statistics before starting the course. ABSOLUTELY NOT THE BEGINNER LEVEL AND NEITHER INTERMIDIATE LEVEL .the course is quiteeeee difficult.

You also need to have a lot of self study , which i am not a big fan of. I hope they make the course more fun rather than a man constantly talking on the screen .

автор: Douglas H

10 апр. 2021 г.

Lectures are good but they expect you to extract too many fine details from them in order to pass the quizzes and assignments. You'd have to watch these oral lessons ten times in order to pass the tests, which are needlessly nitpicky.

автор: Oswaldo C

22 авг. 2020 г.

Los videos no son suficientemente extensos ni para explicar el código, ni para explicar la teoría detrás de los algoritmos, se queda a medio camino de los dos siendo insuficiente en ambos casos

автор: Vjaceslavs M

4 апр. 2021 г.

This course is outdated by few years and not been updated in general with lots of mistakes in assignments and on slides making it very not ejoyable to use.

автор: David C

8 нояб. 2020 г.

Not as good as prev. courses. Univ. of mic. should update or get ride of this module

автор: Paul C

27 мар. 2021 г.

Frankly the quiz questions are ridiculous and no explanation is given why answers are considered incorrect. The wording of the answers is not clear and any from 5 is 120 permutations. You get three attempts and then you have to wait 8 hours. Not great if you are studying part-time. I gave a star for the quality of the video which seemed good although I already know the theory from my university course. However, there was no written material - which again helps answer the questions. This is only a coursera courses, tests should be there to help learning not hinder it.

автор: Topiltzin H

22 мар. 2021 г.

Course was not as expected, I think XG Boost for instance is quite large and was covered in less than 20 minutes.

автор: SAMADRITO B

19 мар. 2021 г.

The course is full of faulty assignment grader and the concepts given are not up to the mark

автор: Aditya M

17 июля 2020 г.

Can't the lecturer use proper slides with proper diagrams for a better explanation.

автор: SHREYAS D

14 авг. 2020 г.

Things in the beginning are not explained properly

автор: Joe R

31 мар. 2021 г.

Terrible lectures - assignments were good though

автор: Konark Y

10 мая 2020 г.

many issues while submitting assignments

автор: Oleg G

16 мая 2020 г.

enrolled by mistake want to u nenroll