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Voltar para Modelos Regressivos

Comentários e feedback de alunos de Modelos Regressivos da instituição Universidade Johns Hopkins

4.4
2,796 classificações
470 avaliações

Sobre o curso

Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Special cases of the regression model, ANOVA and ANCOVA will be covered as well. Analysis of residuals and variability will be investigated. The course will cover modern thinking on model selection and novel uses of regression models including scatterplot smoothing....

Melhores avaliações

KA

Dec 17, 2017

Excellent course that is jam-packed with useful material! It is quite challenging and gives a thorough grounding in how to approach the process of selecting a linear regression model for a data set.

BA

Feb 01, 2017

It really helped me to have a better understanding of these Regression Models. However, I've noticed that there is a video recording repeated: Week 3, Model Selection. Part 3 is included in Part 2.

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26 — 50 de {totalReviews} Avaliações para o Modelos Regressivos

por Rodrigo P

Aug 04, 2017

Very interesting topics and discussions, but not easy to understand.

por Rafael L G

Jun 01, 2017

Great

por Gregorio A A P

Aug 26, 2017

Excellent, but I would be grateful if you could translate all your courses of absolute quality into Spanish.

por Elena C

Mar 03, 2017

A very intense course, where a lot of concepts are introduced. In order for all the new information to be metabolized, it took me much more than four weeks.

por Lopamudra S

Nov 30, 2017

The Regression Models is an excellent course for a beginner.I would recommend the enthusiastic students for a great start in Data science.

por Sadika H

Jan 15, 2017

I really enjoyed this course. I think the toughest for a newbie like me was the second course R programming. But the following courses including this one flow very well and are easy to follow with real life examples. It does get easier after the second course

por Ryan C Y H

Jul 02, 2017

Taught useful things!

por Adán H

Sep 13, 2017

thanks

por Yatin M

Dec 04, 2017

Fantastic course!

por Edgar I

Jan 01, 2017

Muy intuitivo y con excelentes ejemplos!

por Sergio A

Dec 31, 2017

We learn some basic econometrics in this class and how to do basic regression mdels

por john c

Dec 11, 2016

Hard but rewarding work that I think is perfect for Data Science.

por N S N

Jan 02, 2018

Very Exciting Journey of learning and thoroughly enjoyed the course.

por Reinhard S

May 19, 2017

well done!

por Massimo M

Mar 13, 2018

Great course, very informative, with lots of valuable information and examples. Prof. Caffo and his team did a very good job in my opinion. I've found very useful the course material shared on github.

por Chris W

Nov 27, 2016

Great course.

por Andrew K

Mar 13, 2017

Good foundation in the Data Science Certification for Practical Machine Learning. There are 3 areas that I would like to dig deeper so far: Statistical Inference, Regression Models and Practical Machine Learning (perhaps + Deep Learning).

por Albert C G

Sep 02, 2016

Great - learned a bunch

por Farhan M

Feb 26, 2017

Amazing course, I learnt a lot.

por Sai S S

Jul 09, 2017

Thanks much. Good course. Would have loved a tougher final project (eg. using logistic regression). How about adding two variants for all final projects - 1. lots of things to do vs. 2. more technically complex ?

por Berthold J

Jun 24, 2017

Very good lecture and also decent level of difficulties that requires to think/read additional stuff.

por Richard F

Jun 18, 2017

This is the most challenging course so far - new concepts, new approaches and application to a wide variety of situations.

por Samuel Q

May 28, 2018

Excellent course. The instructor is very knowledgeable and covers the most important aspects of regression models. I found myself relying a lot on the text book; unfortunately it contains a lot of typos but its short and easy to follow. The final course project is very open-ended in the sense that its up to the student to make his/her own analysis of the data. A lot of students complain about it but i thought this was great, as it allowed me to push myself to understand the subject better.

por Carlos A C Z

Jan 15, 2018

This was a good course. I learn a lot making the final Project of the course

por Raja J

Nov 19, 2017

Very detailed and exhaustive course