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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: 7,060
Рецензии: 1,287

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:

1076–1100 из 1,265 отзывов о курсе Applied Machine Learning in Python

автор: Maxim P

15 сент. 2018 г.

Nice there could just be a bit more of a case study to see the difference and decision ways in practices

автор: Jesús P S

5 янв. 2018 г.

great course but could be improved with a better explaining of the class on board for abstract concepts.

автор: shashank m

16 июля 2019 г.

Very intuitive course...and carefully designed so that it does not overwhelm the students with details

автор: ZHAI L

11 мая 2018 г.

Compared to previous two courses in this specialization, this course need more time for self-learning.

автор: Justin M

11 апр. 2018 г.

Great course overall. Only reason for 4 stars is some of the assignments could use a bit more clarity.

автор: Manjeet K

14 сент. 2019 г.

Easy to learn the course, just be focussed. Its an applied ML course, not to expect any mathematics.

автор: Ulka K

27 февр. 2020 г.

I found the dataset in the last assignment difficult to interprit. I was hoping for a simpler one.

автор: Stephen R

8 мая 2018 г.

Wish there were a little more theory, realize it's an "Applied" course but still seemed lacking

автор: Michel H

23 янв. 2020 г.

helpfull, but so many information in little time. Difficult to get clarified the ideas behind

автор: Samantha

5 апр. 2020 г.

Very great courses ! It helps to deepen my knowledge in Machine learning. Very recommend it!

автор: Koffi M K

14 окт. 2019 г.

A part from some small issues when doing the last assignment(4), Everything was all right.

автор: Nicholas P

29 дек. 2020 г.

Good content and teacher but needs more interactivity before the final project every week

автор: WhiteCR

15 февр. 2020 г.

Good course for practicing machine learning algorithms with Python Sci-kit Learn package.

автор: Massimo T

12 нояб. 2019 г.

The python packages used in the course are becoming outdated

adding useless difficulties.

автор: soymilk

3 окт. 2020 г.

Contents of lecture are good but the assignments got many problems that should be fixed

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.