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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: 6,856
Рецензии: 1,239

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

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!!

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 1,219 отзывов о курсе Applied Machine Learning in Python

автор: Abdulwaheed M

17 июня 2020 г.

Teaching is very good and it is helpfull

автор: Ramya K

15 июля 2019 г.

Well-organized but assignments too easy

автор: Supratim D

10 авг. 2017 г.

Very informative but bit too difficult.

автор: ROHIT J

2 авг. 2020 г.

very helpfull.thanks for creating this

автор: Xiang C

12 мая 2020 г.

It's good to learn how to use sklearn.

автор: Jagadish C A

18 сент. 2019 г.

Gives good overview of ML using Pyton

автор: Shreekant G

17 июля 2019 г.

Really taught best ML algorithms

автор: xingkong

9 авг. 2017 г.

quiz is harder than assignment.

автор: shreyash t

27 июля 2020 г.

overalll good way to start ml

автор: Vaibhav S

27 мая 2020 г.

way better than last teacher.

автор: Nicolas B

5 июля 2017 г.

Muy buen curso, muy completo.

автор: 李祥泰

14 авг. 2017 г.

Nice courses with nice quiz!

автор: 刘倬瑞

28 июля 2017 г.

Useful, though a little easy

автор: Landon M L

9 июля 2017 г.

the discussion forum is good

автор: Rizvaan M

21 мая 2020 г.

This was a great course.

автор: karim ه

17 июля 2020 г.

Good Course , Thanks!!

автор: Burak

30 сент. 2018 г.

good for scikitlearn.

автор: Bama

11 июля 2020 г.

This course is good.

автор: Abhav T

3 июня 2020 г.

Nice course to study

автор: Shashi K

18 мая 2020 г.

very good learning

автор: hamzaoui m

25 июля 2019 г.

HARD BUT GOOD

автор: Mrs K S

2 окт. 2020 г.

nice course

автор: Aditya V

3 июля 2018 г.

Excellent!!

автор: ISHAN H S

23 июля 2017 г.

Awesome !!!

автор: KILLANI T

10 июня 2020 г.

hard a bit