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

7,721 calificaciones
1,413 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

26 de nov. de 2020

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 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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401 - 425 de 1,397 revisiones para Applied Machine Learning in Python

por Deepak G

24 de jun. de 2020

A very nice course to get involved with the data from good resources and with great insights to draw from those.

por Yuwei Y

4 de jun. de 2019

I like this course very much. It focuses on ML application and it's easy to understand. Definitely recommend it!

por Vasilis S

12 de ago. de 2018

Great course! Assignment 4 is very interesting and allows you to apply all you've learnt in this course at once.

por Ryan J

11 de feb. de 2018

Incredibly insightful and helpful for a recent master's graduate looking to augment his skills on the job market

por Matthias B

5 de ago. de 2017

Great course, very hands-on. Maybe difficult to follow without any prior knowledge in machine learning, though.

por Eduardo L L

12 de nov. de 2021

I​t's a really good course. I teaches you the basics of many ML algorithms. I really recommend it for begginers

por Diego C

31 de mar. de 2021

Very good introduction, a lot of information but you feel you are learning the foundations of machine learning.

por Andrii T

13 de jul. de 2020

Excellent course. I'm particularly thankful to the instructor, who was warm-hearted and explained well enough.

por Siddhant T

9 de ago. de 2021

A​mazing ocurse focussing on handon application of machine learning alorithms and tools for model evaluation.

por Liu L

2 de ene. de 2019

This course provides a good introduction to using python in machine learning. It helps me to get hands on it.

por Mikhail S

27 de ago. de 2017

Thank you for the very well done course! It's really helpful, has a clear explanation of topics and examples.

por Ahmad A

11 de jul. de 2020

Excellent Course each topic is both theoretically as well as as practically explained. Really a good course

por Akshay S T

24 de may. de 2020

Very Intuitive and helpful course for clearing concepts of machine learning and Python's SciKit Learn module

por Nitin K

22 de abr. de 2019

Great Course. Helped me to learn the concepts of Machine Learning and uses of respective Sklearn libraries.

por Mohamed A M A

19 de ene. de 2019

The theoretical part is comprehensive with an excellent balance between the theory and practical exercises.


5 de nov. de 2018

Excellent collection of various types of Machine Learning Algorithms with visual demonstration and example.

por Thomas S

21 de jun. de 2021

A very good review of important fundamental concepts in Machine Learning focusing on the usage of Sklearn.

por Rahul S

8 de dic. de 2019

This course is Beautifully crafted to cover most of the important concepts of supervised machine learning.

por Christian E

19 de ene. de 2019

Content and phase are very good. Very clear explanation of topic by the instructor. Appreciate it so much.

por Lari L

3 de jul. de 2021

The course gives deep knowledge on the subject as well as best practices and strong practice assignments.

por abdelrahman a

9 de dic. de 2020

the most interesting thing in the course was treating the students as if they are already data scientists

por Anurag W

18 de jul. de 2019

This Course really provides great learning on Advance Machine learning techniques with Python application

por Matt E

29 de ago. de 2017

Learned a lot in this course! Much better than the previous two and also taught by a different professor.

por Fettah K

9 de may. de 2021

Taking these lessons from some of the world's most prestigious universities and professors is priceless.

por Alexander A

16 de ago. de 2020

Excellent Course. The only one problem is the duration of videos. The codes in Jupyter are very elegants