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

4.6
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7,522 calificaciones
1,372 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

AS
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.

FL
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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326 - 350 de 1,358 revisiones para Applied Machine Learning in Python

por Aino J

21 de jun. de 2020

Practical, applied, and a good overview of how to apply different (mainly supervised) machine learning algorithms using python scikit-learn.

por Santhana C

5 de ago. de 2017

Nice Course! Lots of useful information packed in 4 weeks. Be prepared spend some extra time if you want to really benefit from this course.

por Eddie G

18 de ene. de 2021

This course has the perfect combination of theory and practice. It's Intense for a beginner In machine learning but Is absolutely worth It.

por Rajendra S

11 de ene. de 2019

This course is the one that I enjoyed most while learning anything in Coursera. Thank you everyone associated with this course and content.

por Juan R C C

25 de oct. de 2017

Good course, content and teaching. Very good weekly assignments allow students to well consolidate course contents on real world practices.

por Nattapon S

3 de ago. de 2017

It is a good class. I learn a lot from this course. It is a concise starting course for Python machine learning. I recommended this course.

por Jose A P A

14 de jul. de 2020

Un excelente curso para reforzar lo aprendido en el curso Minería de Datos para la Toma de Decisiones que se dicta en la Universidad Esan.

por Ramon S

7 de dic. de 2020

Excellent! I had previously done a course on machine learning and it left me with big holes in my knowledge, this really clear things up!

por Moustafa S

28 de jul. de 2020

GREAT COURSE!, this is one of the greatest courses for applying machine learning and data science algorithms and skills, great great job.

por Ritesh P N

19 de jul. de 2020

It was amazing course for applied machine learning. The tutor was good teaching core concepts of machine learning algorithms step by step

por Chak W

8 de sep. de 2018

Great Course with high practicality. Need more lectures on how to process categorical data. Read the Forum if you encounter any question!

por Fengping W

28 de mar. de 2018

It is really a good one, and I learn a lot here, both for theory and applied skills. And the reading materials are really good resources

por Shuyi Y

27 de jun. de 2017

This course is great because I received so much training in applying the ML packages and functions python. A lot of hands-on experience!

por Marcelo P

9 de jul. de 2019

Great course! Superb professor! Very well organized and structured. Lots of useful optional articles and videos. Learned a lot. Thanks!

por Nguyen K T

25 de jun. de 2019

A very practical course and it helps me to understand more about machine learning theory. After all, this is a great course. Thank you.

por Mehmet F C

27 de dic. de 2018

good one to quickly start learning ML - covering models, what they do, and how to tune them. Not going deep into the "how" models work.

por Shao Y ( H

8 de sep. de 2017

Very good survey of all fundamental topics of machine learning! Good resources for preparation for technical data science interview! :)

por INHOI J

25 de abr. de 2020

Great course. Professor delivered very complicated concepts of machine learning very easily. Quiz and assignments were very helpful.

por Keith M

12 de oct. de 2020

Excellent course. Very detailed, very interesting, a lot to get through in each week. Lots of great examples of code and scenarios.

por Quan S

8 de may. de 2019

Course materials are very systematic and instructive, and the professor teaches very clearly. I like this course and recommend it.

por Flavia A

11 de mar. de 2018

Practical class to learn well-known models and scikit-learn. The practice tests are great to help you move from theory to practice.

por Aniket S K

1 de jul. de 2020

Good Course. Not for beginners starting with Machine Learning. Intermediate level. Prior knowledge of python libraries would help.

por Émile J

19 de may. de 2020

The exercices and evaluations are more complex than in the previous courses in this short program, but also much more instructive.

por Himanshu B

15 de may. de 2020

It was really an excellent well designed course, I gained valuable information that I will use as a business analytics in future.