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Вернуться к Applied Machine Learning in Python

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

Оценки: 7,147
Рецензии: 1,297

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

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.

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:

1251–1275 из 1,276 отзывов о курсе Applied Machine Learning in Python

автор: Rohit S

21 мая 2020 г.

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

автор: Gilad A

27 июня 2017 г.

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

автор: Sai P

3 июня 2020 г.

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

автор: Philip L

30 окт. 2017 г.

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

автор: Pakin S

10 янв. 2020 г.

How can i pass without reading discuss about problem with notebook

автор: Hao W

27 авг. 2017 г.

The homework is too easy to improve our understanding of ML

автор: M S V V

29 июня 2020 г.

Too much of information compressed within a short span.

автор: José D A M

21 июня 2020 г.

Too fast, yet too difficult. Needs deeper explanation.

автор: Navoneel C

21 нояб. 2017 г.

Nice and Informative but not practically effective

автор: Priyanka v

8 мая 2020 г.

if it is more detailedthen it will be more useful

автор: Sameed K

15 мар. 2018 г.

have to figure out a lot of things on you own.

автор: Andy S

4 июня 2019 г.

It could have been better with more examples.

автор: Shan J

12 апр. 2020 г.

The explanation could have been much better.

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 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: 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: David C

8 нояб. 2020 г.

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

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: Konark Y

10 мая 2020 г.

many issues while submitting assignments