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Avis et commentaires pour l'étudiant pour Apprentissage mechanique pratique par Université Johns-Hopkins

4.5
2,578 notes
483 avis

À propos du cours

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....

Meilleurs avis

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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76 - 100 sur 475 Examens pour Apprentissage mechanique pratique

par Jose R C

Aug 16, 2016

The machine learning course every Data Scientist should do.

par Felix A

Sep 20, 2016

Unexpectedly challenging and insightful.

par Dimitrios G

Jul 07, 2017

Amazing course. Short videos packed with information!

par Chris H

May 23, 2016

Great course. I really enjoyed working on the prediction project at the end.

par Policarpio S

Mar 28, 2016

I really enjoyed this course. The material was concise and allows me to get up and running with ML.

par 朱荣荣

Apr 26, 2016

good and useful!

par Chris N

Jun 07, 2017

loved it - fascinating subject and more detail than you could possibly want from the course instructors. Friendly community in the forum too.

par Abhishek S

Aug 15, 2017

Excellent course.

par PATRICK

Mar 02, 2017

Nice, clear and concise.

par hyunwoo j

Apr 10, 2016

johns hopkins' courses very helped me

par Jitender K

Jun 03, 2016

A very good course.

par Roberto D

Jun 20, 2017

Methods to be applied in preparation for creating a data product.

par Neven S

Jan 22, 2016

Very good!

par Dale H

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.

par Xray W

Mar 21, 2016

Principle and practices. Good coverage on topics to get you started!

par Prohnițchi V

Dec 31, 2017

Great course. A lot of extremely useful stuff.

par Monnappa

Nov 12, 2016

Good content as an introduction to Machine learning!

par Donson Y

Sep 04, 2017

This is a fantasy course to know that how to build your first machine learning model.

par Bill K

Feb 10, 2016

Really good class. I think there were some small issues with the class project. Like all real world problems it was not entirely well specified and the data was a bit odd to use for a prediction exercise because it was time series data.

par MD A

Jan 12, 2017

Excellent and useful course.

Some of the materials covered in Week 4 should be distributed to earlier week(s). The current Week 4 video coverage, quizzes, and the course project on accelerometer data is too much for the week, esp. if the student has lookup and review some key concepts from the resource links in the video slides. Video lectures are informative and easy to follow, although somewhat rushed in Week 4.

par Harris P

Jan 16, 2017

It was like opening up a door to a whole new world. I have discovered new tools that I will thoroughly enjoy to use for the exploration of data and for predictions. Thanks Team Coursera !

par Gary R S

Dec 31, 2017

Excellent intro to machine learning with interesting projects.

par Sebastian F

Jan 24, 2016

Great course. Really educational and informative. Well taught too!

par Rudolph A M

Oct 21, 2016

Wonderful!

par Angel D

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.