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

4.5
2,639 notes
498 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.

AS

Aug 31, 2017

Highly recommend this course. It makes you read a lot, do lot's of practical exercises. The final project is a must do. After finishing this course you can start playing with kaggle data sets.

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126 - 150 sur 489 Examens pour Apprentissage mechanique pratique

par Robert K

Sep 26, 2017

A great introduction to machine learning and it does a good job building on the material from the previous classes.

par benjamin s

Jul 09, 2018

Probably the most enjoyable course of the specialisation, more maths would improve the quality of the content

par Jay S

Aug 27, 2016

Excellent introductory course to Machine Learning. Very informative materials. Prof. Leek is a great teacher.

par Jerome C

Jan 17, 2017

excellent course. Be prepared to learn a lot if you work hard and don't give up if you think it is hard, just continue thinking, and interact with other students and tutors + Google and Stackoverflow!

par Jorge M A A

Apr 13, 2016

I enjoyed a lot this module, I'll use at my daily work some of the features I learned

par Edward R

Dec 17, 2017

Great course, but it may take you more than the allotted 4 weeks if you intend to dig a bit deeper and pursue some of the additional resources referenced throughout the course. I would definitely recommend doing that, as there is A LOT of material to cover if you, like me, just have to know the details of what's happening behind the scenes.

par Billy J

Apr 13, 2016

Excellent introduction to machine learning. I feel that I have a good basic foundation to start building upon.

par Arunkumar M R

Sep 30, 2017

Awesome course. Super effective quizzes.

par Nirav D

Apr 02, 2016

This is a very useful course in Machine Learning that teaches us how to use the R based packages such as CARET for applying machine learning techniques. The course project helps understand how these techniques are applied in real world applications and develop useful insights.

par Supharerk T

Mar 07, 2016

I want to learn ML in R so I go straight to this course without taking any other course in this specialization, and it doesn't disappoint me. Thanks for a great course!

par Pei-Pei L

Jul 27, 2017

This course covers a lot of information in a short time, but you'll feel very proud of yourself when you finish it! It made me feel much more comfortable with writing machine learning programs, and am ready for the next topic!

par Florian

Jul 09, 2016

Great primer for machine learning with ample additional resources for those who are interested. I feel this course gave me a solid basis to delve deeper into the topic.

par alberto p

Mar 08, 2016

Very practical and goal-oriented

par Nikhilesh J

Mar 02, 2018

Provides a quick and dirty look at Machine Learning. An easy way to get started.

par Avirup N

Mar 07, 2016

Very informative

par Pam M

May 19, 2016

Good material, presented in an organized fashion. I was able to apply what I learned immediately in a work setting.

par Fernando S e S

Jul 24, 2016

It's hard as hell, and very good.

par Jair G

Jan 20, 2017

Top 3 course of this specialization.

par Joseph

Dec 13, 2016

Awesome course. Jeff Leek does a truly amazing job at explaining very complicated concepts thoroughly and quickly. I'm surprised we went through as much material as we did. Out of the 9, this is one my favorites.

par Javier A D

May 27, 2018

References were very usefull for doing deep analisys in the thems

Quices were challenge.I learn a lot solving them.

I mis the swirl sessions

par Ilia

Apr 27, 2016

One of the most valuable courses in the specialization!

par Aleksey K

Feb 10, 2016

Made many things clear. Perhaps, the best class in the series.

par Martin S

Feb 26, 2016

Very practical tools and also very encouraging!!

par Camilla J

May 12, 2018

This course was really informative and extremely efficient by letting you know just the few basics needed to build some quite advanced models such as random forest..

par Madhuri

Mar 23, 2016

I like the organisation of the course. The first video is so informative yet so simple. Great resources have been listed in it and so subtly. Also I saw the organization of folders and lecture notes and everything in Github repo for this course. It s awesome. I keep stuff like that.. well numbered and everything. I really appreciate it as it makes life of a student lot easier. Thanks.