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Volver a Predictive Modeling and Machine Learning with MATLAB

Opiniones y comentarios de aprendices correspondientes a Predictive Modeling and Machine Learning with MATLAB por parte de MathWorks

4.7
estrellas
29 calificaciones
13 reseña

Acerca del Curso

In this course, you will build on the skills learned in Exploratory Data Analysis with MATLAB and Data Processing and Feature Engineering with MATLAB to increase your ability to harness the power of MATLAB to analyze data relevant to the work you do. These skills are valuable for those who have domain knowledge and some exposure to computational tools, but no programming background. To be successful in this course, you should have some background in basic statistics (histograms, averages, standard deviation, curve fitting, interpolation) and have completed courses 1 through 2 of this specialization. By the end of this course, you will use MATLAB to identify the best machine learning model for obtaining answers from your data. You will prepare your data, train a predictive model, evaluate and improve your model, and understand how to get the most out of your models....

Principales reseñas

SS

Sep 14, 2020

Extremely helpful and interesting course.\n\nThe basic concepts and further learnings are well addressed by the instructors.\n\nHighly recommended course for Machine Learning.

AH

Sep 11, 2020

Very practical, but still high-level view to manage such projects. Testing was sufficient to test a full understanding. Thanks, I learnt a lot.

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1 - 13 de 13 revisiones para Predictive Modeling and Machine Learning with MATLAB

por MICHAIL E T

Aug 30, 2020

This is an excellent course, in which participants are able to understand supervised machine learning algorithms. As it combines knowledge from the previous courses, all the courses are linked in a great way. The prospect of this course, as well as all of the courses in this specialisation, is that it is based on real data making the interpretation of the results much more realistic. In terms of the sound, video and material quality, they are excellent. Thank you!

por odile w

Sep 26, 2020

The mathworks team did it again. This is an amazing course. I am a QM reviewer, and I can tell you that this course would get high marks when it comes to the quality of the organization, videos, and other materials. It is a mooc, and as all moocs, you get as much as you put into it.

por Muhammad N A

Oct 05, 2020

The most captivating and useful course so far in this specialization! I barely managed to complete the last week of course 2 because it was irrelevant for me, but I'm so glad I continued! Looking forward to the capstone project

por Shaktiyavesh N P S

Sep 14, 2020

Extremely helpful and interesting course.

The basic concepts and further learnings are well addressed by the instructors.

Highly recommended course for Machine Learning.

por Andre H

Sep 11, 2020

Very practical, but still high-level view to manage such projects. Testing was sufficient to test a full understanding. Thanks, I learnt a lot.

por John N D

Oct 26, 2020

Great Course and very helpful. Good to be able to put hands on real data and exercises.

por Paras N

Sep 22, 2020

I am so glad I did something new.

and I am waiting for the data science project...

por Luis H S

Sep 17, 2020

As always, a fast-paced course with crystal clear explanations!

por Fredrik E

Oct 04, 2020

Fantastic course to learn more about MATLABs ML capabilities

por Venkata S N A

Oct 08, 2020

Good content and interesting examples

por Jan-Hein Z

Sep 09, 2020

A good course , you learn the workflow and principles of regression and classifications .

And gain knowledge of the fashionable words like "lasso regression" . "k fold validations" and KNN classification or regression . And always the bias :)

por George T

Oct 16, 2020

The course was an excellent introduction to Modelling and Machine Learning with MATLAB. Course weaknesses are: (a) the low quality of MP4 downloads, and (b) the inability to download PDFs of the theory background material

por Ezra S

Sep 06, 2020

A way to improve is to have the course materials not all over the place. For example, compile everything related to modelling (both via app and codes) in ONE place (in one week). That way, it is easier to follow. Also, each speaker seems to use different codes (although it has same outcomes). All speakers can prepare the codes in the same way (same coding) so that students do not get confused. Overall, my experience with the course is good.