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

4.5
2,637 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.

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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201 - 225 sur 489 Examens pour Apprentissage mechanique pratique

par Francisco J D d S F G

Nov 27, 2016

The best course of the specialization along with the statistical inference one - the final assignment is very fun to do, pretty much like a Kaggle competition.

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 hyunwoo j

Apr 10, 2016

johns hopkins' courses very helped me

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 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 PRAKASH J M

Dec 25, 2017

Pushed me to learn and experiment and make mistakes. Thank you

par David S

Feb 07, 2016

The course gives a clear explanation of why machine learning, with a goal of prediction, is different from regression. The use of the caret package in R is emphasized. Caret provides a uniform interface to many different machine learning algorithms, leaving no excuse for practitioners not to test a variety of approaches to confirm the robustness of their conclusions.

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 Ivan Y

Mar 06, 2018

great intro to machine learning!

par sampath

Oct 13, 2017

Tough but very good course

par Raju G

Nov 26, 2017

Extremely useful.

par Evgeniy Z

Apr 12, 2016

Nice course.

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.

par SATHYANARAYANAN S

Sep 11, 2017

Very good for anyone wanting to get into the field of Data Science using R

par Marcus S

Feb 11, 2016

Great introduction to the subject with good classification examples using R.

par Massimiliano F

Feb 17, 2017

In my opinion, the best course of the entire Data Science Specialization

par benjamin s

Jul 09, 2018

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

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 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 Billy J

Apr 13, 2016

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

par manny d

Sep 10, 2017

Best course i have ever taken on Machine Learning! Excellent presentation and excellent reference sources. Machine Learning is not that hard as I thought it would be..please make more practical courses like this one.

par Nikhil K

Feb 19, 2016

Some of the terms used here vary from the terms used in the industry. For example recall, precision etc. Overall this is a very good course with provides basics of machine learning.

par andy p

Aug 10, 2016

Great topic with a great instructor. Only wish the program was a little longer to spend some more time on some of the models.