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Avis et commentaires pour d'étudiants pour Apprentissage mechanique pratique par Université Johns-Hopkins

3,058 évaluations
580 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

13 août 2020

recommended for all the 21st centuary students who might be intrested to play with data in future or some kind of work related to make predictions systemically must have good knowledge of this course

28 févr. 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.

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76 - 100 sur 570 Avis pour Apprentissage mechanique pratique

par Camilla J

12 mai 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 Nicholas A

30 mars 2018

This was my favorite class of the specialization. It was taught very well, and I felt like everything I learned in the previous classes were finally coming together.

par Pablo L

20 sept. 2018

Excelent course, it's a little bit short considering the breadth of the topic, but covers the most important algorithms and never abandon it's focus on methodology.

par Rachit K

16 sept. 2017

The course gets you deep into ML very quickly ...but I think that's enough to get someone introduced to machine learning. The recommended book a great accompaniment

par Hiran H

4 juin 2020

This is by far the best machine learning course I took. This course is more hands-on "Machine Learning" kind rather than providing just a bunch of videos to watch.

par Emanuele M

15 nov. 2016

It very well done, good pace, and gives you real and concrete elements and examples to build a fully functional machine learning algorithm! i recommend this course

par Piotr K

23 oct. 2016

Nice introduction to machine learning in R. It is rather basic level, so it not for people that already know some basics related to regression and classification.

par Jan K

2 août 2017

A nice overview of the most popular Machine Learning algorithms. Also very thorough, given the limited amount of time. I recommend anyone interested to take it!

par Francisco J D d S F G

27 nov. 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 David R

14 janv. 2019

Great introduction to Machine Learning in R. Concepts explained very clearly and project gave opportunity to test out the concepts introduced to real data.

par Vinicio D S

22 mai 2018

You will learn how to use the caret package and learn how to implement ML algorithms. If you want the theory behind it, you need to go to other courses

par Selim J R

15 déc. 2016

Excellent course. I feel like i know so much already even though we scratched the tip of the iceberg. Will definitely enroll in more advanced courses.

par Pouria T

2 juil. 2017

Great course, thank you. I was able to use what I have learned from the previous 7 courses and see them on in action through this course. Thank you :)

par Sinan G

29 mai 2017

Very fine course in machine learning where the focus is more on the use of ML rather on the theory behind it i.e. the course title fits its contents.

par Deleted A

1 déc. 2019

The course is amazing. The use of training and testing to predict data analysis made me more fascinated and interested in Data Science. Very nice!

par Jerome S P

18 juin 2019

Very good explanation! Trying to do the examples help me understand more plus the explanation which is not on the slide helps a lot. Thank you

par Shashikesh M

3 août 2017

An absolute approach of learning machine learning in very unique practical manner. Fundamental at the same to very practical learning course.

par Chris N

7 juin 2017

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

par Matthew W

1 mars 2016

High level and brief overview but found it informative introduction into machine learning with R. The final project is fun and interesting.

par Javier A D

27 mai 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 Swaraj M

5 mai 2020

Thank you coursera for helping to get the fundamentals of machine learning, now I am confident enough to switch my career in data science.

par Laro N P

22 juil. 2018

Good course, I miss more practice exercise because theory is always welcome but when we are capable to understand is doing real practice.

par Sanjay J

6 oct. 2020

Fantastic course, and loved the hand's on projects and assignments. Good course to practically get started in machine learning using 'R'

par Gustavo S

19 avr. 2020

Very nice course, well-explained, sometimes a little bit fast if you dont have the luck of having previous knowledge.

100% recommendable

par Nathan M

11 juin 2016

Extremely useful class! Jeff also has many excellent suggestions for resources that will teach you even more about machine learning.