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Opiniones y comentarios de aprendices correspondientes a Applied Machine Learning in Python por parte de Universidad de Míchigan

7,973 calificaciones
1,452 reseña

Acerca del Curso

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....

Principales reseñas


8 de sep. de 2017

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


13 de oct. de 2017

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!!

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1201 - 1225 de 1,442 revisiones para Applied Machine Learning in Python

por Ekun K

16 de jul. de 2020

This is a great course. I recommend using the Introduction to Machine Learning book to complement the lecture videos.

por Wynona R N

23 de jun. de 2020

Good introduction course on machine learning algorithms. The books and the readings are recommended to look through!

por Amanda V

2 de jun. de 2018

You will learn a lot. But the course is a little bit fast for regular students. Assignments deal with real problems.

por Rohith S

16 de nov. de 2017

A few more code examples would have helped better understand various packages provided by Python and how to use them

por lcy9086

2 de feb. de 2019

Great course on doing machine learning use sklearn and put little but enough explanation of the theories behind it!

por Alexandr S

24 de feb. de 2019

It would be nice to have more practical assignments like the last one! Anyway it was very interesting! Thank you!

por Bharat G

30 de ago. de 2017

Amazing Course but Please add some more theory and concepts in Neural Networking.Overall it is a good experience.

por Alpan A

27 de nov. de 2019

Very good curriculum with a hands on project. However thera are some limitations with the platform with grading

por Amine T

21 de jun. de 2017

Complete course on supervised learning

Would be nice to cover PCA and unsupervised learning in the assignments

por Andres V

16 de oct. de 2020

the final assignment was too hard compared to the other assignments and the contens given in the last module

por CMC

9 de feb. de 2019

A little dated. Overall a good introduction. The informal explanation of SVM was particularly effective.

por divya p

4 de sep. de 2020

course is very informative with hands on details, assignments and quizzes are very useful for assessment

por Maxim P

15 de sep. de 2018

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

por Jesús P

5 de ene. de 2018

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

por shashank m

16 de jul. de 2019

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

por ZHAI L

11 de may. de 2018

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

por Justin M

11 de abr. de 2018

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

por Manjeet K

14 de sep. de 2019

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

por Ulka K

27 de feb. de 2020

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

por Vishwa M

3 de sep. de 2021

Course Content was excellent. I really learned a lot. Assignment 4 was a hassle to submit though.

por Stephen R

8 de may. de 2018

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

por J N

23 de may. de 2021

Teaching by the professor is very good and i learnt every thing from scratch thankyou coursera

por Pierre D

1 de may. de 2021

Interesting course. Last exercise allows understanding how to use ML, when you are all alone.

por Michel H

23 de ene. de 2020

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

por Samantha

5 de abr. de 2020

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