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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
2,572 classificações
481 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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251 — 275 de {totalReviews} Avaliações para o Aprendizagem Automática na Prática

por asma m

Oct 02, 2018

The professor has a very clear lecture, brief and persistent comparing to others. I just love this course .

por Kidpea L

Oct 04, 2018

tx

por Rahimullah S

Oct 28, 2018

thank you, this class is very practical and informative. The projects are a little complicated but very practical.

por Suresh R

Oct 31, 2018

Very good course

por Keidzh S

Jul 15, 2018

Practical Machine learning helped me to achieve my personal goals. Algorithm of prediction became clear, that gives the understanding of main point of the data science.

por Oleksandr K

Jul 11, 2018

Great course! However, it would be good to learn about artificial neural networks as well.

por Theodoros M

Jul 10, 2018

Practical ML is a great course, that provides training in the practical aspects of the topic.

por Dora M

Mar 30, 2019

Really enjoyed this class and learned a lot!

por Matthew S

May 08, 2019

Good introduction to machine learning. Provides pretty comprehensive coverage of major algorithms and approaches.

por Nino P

May 24, 2019

It's good that they teach you basics of machine learing in R (caret package), but it's very introductory course. I definetly recommend this course to beginner, but I also recommend taking more courses on this topic (Andrew Ng's for example).

por YANAN D

May 27, 2019

elementary course and not too much work

por Jeffrey M H

Jun 10, 2019

So far, one of the most fulfilling courses in the Data Science specialization!

por Jerome S P

Jun 18, 2019

Very good explanation! Trying to do the examples help me understand more plus the explanation which is not on the slide helps a lot. Thank you

por Don M

Jul 15, 2019

A fast-paced course that got me going in building models and understanding the pitfalls. I felt the directions for the final project were somewhat poorly worded and vague (and calling one of the files test when it was not to be used for testing the model was initially confusing), but overall it was good. I would have liked to have seen the final project uploaded as a secure file as has been done in other courses, and Github was a poor platform for viewing html files. Additionally, the question about out of sample error caused many people problems in the projects as they confused it with with Accuracy, yet it was weighted heavily in the rubric: I'd like the instructors to review the materials how that material is presented in terms of models. I got 100%, but as always you have to pay very close attention to the rubric.

As always with this specialization, you are really just given a taste and there is no way you can fully explore all the material and references presented., but it is enough to get you going and wanting to come back and explore the material more.

por Andrew

Jul 24, 2019

Great intro to machine learning. Covers the basics to allow you to being using ML concepts on your own.

por Klever M

Jul 29, 2019

It was a great overview of the fascinating word of ML.

por Gustavo C G

Aug 07, 2019

Excellent introduction to machine learning. Great examples and detailed explanations, as usual

por Martin G

Aug 13, 2019

Excellent course

por Deogratias K

Aug 16, 2019

I liked everything abt it

por Khalid S A

Aug 18, 2019

excellent course and very beneficial

por Sulan L

Nov 19, 2018

I hope we can have more détails in this cours and to see how to use the algorithms for the big data. Thank you.

por Diego T B

Nov 07, 2018

Very useful. The models were very easy to understand

por Terry L J

Nov 09, 2018

Lot of good material, however, on all of these courses, it would be very helpful if they were better organized for learning.

Overview of learning objectives in a step sequence for a more organized approach for learning (maybe even a process roadmap map sequencing activity to follow that you can reference back to.

Detailed information for each step in the learning process that can be followed that maps back to the roadmap.

A summary of the learning objective in the roadmap sequence.

Basically, just like writing a paper, > overview/objectives > Main topics >subtopics, etc. > summary

por Sakib S

Mar 15, 2019

Include more swirl practice problems.

por Shobhit K T

Dec 18, 2017

Great course with practical insights on machine learning