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Voltar para Aprendizagem Automática na Prática

Comentários e feedback de alunos de Aprendizagem Automática na Prática da instituição Universidade Johns Hopkins

4.5
2,610 classificações
492 avaliações

Sobre o curso

One of the most common tasks performed by data scientists and data analysts are prediction and machine learning. This course will cover the basic components of building and applying prediction functions with an emphasis on practical applications. The course will provide basic grounding in concepts such as training and tests sets, overfitting, and error rates. The course will also introduce a range of model based and algorithmic machine learning methods including regression, classification trees, Naive Bayes, and random forests. The course will cover the complete process of building prediction functions including data collection, feature creation, algorithms, and evaluation....

Melhores avaliações

AD

Mar 01, 2017

Issues of every stage of the construction of learning machine model, as well as issues with several different machine learning methods are well and in fine yet very understandable detail explained.

DH

Jun 18, 2018

Excellent introduction to basic ML techniques. A lot of material covered in a short period of time! I will definitely seek more advanced training out of the inspiration provided by this class.

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351 — 375 de {totalReviews} Avaliações para o Aprendizagem Automática na Prática

por Craig S

Feb 12, 2018

Not as detailed as some others in the specialization which is a shame but good none the less. The videos go through the info quickly so be prepared to go back over.

por Robert R

Jul 20, 2016

Just the right level of detail

por Jeffrey E T

Mar 28, 2016

Good overview of available techniques and the Caret package. Will get you started in machine learning.

por Steve d P

Mar 20, 2016

Nice, other courses will go more in depth though.

por Eric L

Jun 02, 2016

Great course, very high paced with a lot of information. would have been great to add two more weeks and another project to use more machine learning

por Carlos R

May 27, 2018

Great Course! I have learned a lot of new things.

por Carlos S

Jan 31, 2016

First and foremost I'm so thankful for the exposure to so much material in such a condensed schedule. Very good class. Even though I had to muscle my way through it.

I think the class could be improved with one additional discussion thread for the project.

A guide similar to the ones created for Inferential Statistics and Regression would also have been very helpful.

I benefited immensely from reading parts of the book "An Introduction to Statistical Learning" while taking this course.

por Swapnil A

Jun 09, 2017

The course covers few important topics in R like cross validation, decision trees, random forest etc. which comes in very handy for a data science aspirant. It expects the participant to have a descent knowledge in R. Overall, I am pretty satisfied with this course. Thanks!

por Greig R

Nov 14, 2017

Good course, I learnt a lot. It does need to be updated with more modern versions of software.

por Rahul K

Mar 07, 2016

Really Well Structured Course!!

por João R

Aug 20, 2017

Got confused how to perform cross validation and when. Other than that, very practical. Great job.

por Lucas

Jun 03, 2016

This course allows you to implement practical solutions using machine learning algorithms without having to know the mechanisms behind the calculations in detail. Unfortunately questions in the discussion forum were quite rare and many questions were not resolved during this course.

por Chris M

Aug 14, 2016

Unlike the rest of the modules in this specialisation, this one was well taught, a good blend of theory and practice and well paced.

There were still a few issues with wording in quizzes (and some where there seemed to be two identical answers to one question, where one would be considered right and the other wrong - purely chance). In addition, the lack of consistency in how to submit assignments across the specialisation is frustrating, I'm not sure if it's supposed to be a way to show how to use github or something like that, but it shouldn't be the case.

por bhawani p

Jan 07, 2017

briefly summarised the machine learning algorithms. Good place to start!

por Rohit P

Nov 13, 2016

Lectures were not very detailed.

Quizzes were good and challenging, but too many times the results didn't match the answers even when the random seed was set right

Final project should have been more challenging with more models to build and compare

por Aashaya M

May 29, 2016

In my opinion this course is highly technical and demanding in nature compared with the others. The learning experience is good and coursera.org has given a opportunity for customization ! thank you Coursera

por Kamran H

Feb 18, 2016

Pretty good overview of how to build some types of machine learning models through the caret library in R, but not much in terms of the theoretical underpinnings or why one method is better than the other or where it is most suitable.

por Bassey O

May 03, 2016

Very informative course.

por Jikke R

Aug 11, 2016

Very enjoyable and generally quite understandable introduction to machine learnings with hands-on approach through the course project. It was a bit too fast-paced and generic for my liking, but many options were offered and highlighted for finding additional learning documents and courses to be able to deepen the knowledge acquired in this course.

por Tongesai K

Feb 08, 2016

Very good course. I am very knew to this topic but am sure will find a lot of application in my speciality - geophysics

por Yew C C

Feb 04, 2016

Wish to have more systematic structure, detail information and hands-on exercises.

por Daniel U

Feb 17, 2016

Fast paced and little focused on the algorithms but quite useful overall.

por Yukai Z

Dec 09, 2015

A good introductory course for people who has an interest in knowing the principles of machine learning and want to make a step forward. Sufficient details covered throughout the course and additional resources were provided which are very useful. Quizzes were well designed with minor improvements in the accidental mismatch of the answers due to package version issues. Overall the study experience was enjoyable and would definitely recommend to someone who wants to start knowing data science.

por danxu

Mar 14, 2017

very good, but if it has swirl practice like th other courses it would be perfect.

por Bruce I K

Oct 20, 2016

It's a great course but I hope you add a few things. The course about the machine learning algorithm is so basic. Please get deep into the machine learning algorithm. Then it would become the perfect course.