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Practical Machine Learning, Johns Hopkins University

4.5
2,220 classificações
434 avaliações

Informações 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

por 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.

por 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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428 avaliações

por André Caetano Luna

Dec 13, 2018

very good practical experience using machine learning models, especially regarding PCA usage

por Carlo G Inovero

Dec 04, 2018

thank you

por Javier Eslava Schmalbach

Dec 02, 2018

Excellent.

por Sulan LIU

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 Raunak Shakya

Nov 19, 2018

a very good course for those wanting to learn Machine Learning to implement in Data Science.

por German Rafael Mejia Salgado

Nov 14, 2018

Este es un muy buen curso, aprendes lo básico para poder entrar en el mundo del machine learning y te da la oportunidad de desarrollar modelos realmente útiles.

Recomendado, definitivamente.

por Naman Khurpia

Nov 13, 2018

please remove the checking by students

por Alfonso R Reyes

Nov 13, 2018

Hands on course. Loved it. It goes a little bit fast, however, the content is ambitious.

por adam reiner

Nov 11, 2018

Best course in the data science series. It is practical, so if you are looking for something theoretical this will not be the course for you. Also good introduction the methods for model testing and validation.

por Terry L Jones

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