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Opiniones y comentarios de aprendices correspondientes a Supervised Machine Learning: Classification por parte de Habilidades en redes de IBM

4.9
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221 calificaciones

Acerca del Curso

This course introduces you to one of the main types of modeling families of supervised Machine Learning: Classification. You will learn how to train predictive models to classify categorical outcomes and how to use error metrics to compare across different models. The hands-on section of this course focuses on using best practices for classification, including train and test splits, and handling data sets with unbalanced classes. By the end of this course you should be able to: -Differentiate uses and applications of classification and classification ensembles -Describe and use logistic regression models -Describe and use decision tree and tree-ensemble models -Describe and use other ensemble methods for classification -Use a variety of error metrics to compare and select the classification model that best suits your data -Use oversampling and undersampling as techniques to handle unbalanced classes in a data set   Who should take this course? This course targets aspiring data scientists interested in acquiring hands-on experience with Supervised Machine Learning Classification techniques in a business setting.   What skills should you have? To make the most out of this course, you should have familiarity with programming on a Python development environment, as well as fundamental understanding of Data Cleaning, Exploratory Data Analysis, Calculus, Linear Algebra, Probability, and Statistics....

Principales reseñas

NR

21 de feb. de 2022

Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.

AP

28 de feb. de 2021

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!

Keep up the good work. You guys are helping the community a lot :D

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1 - 25 de 51 revisiones para Supervised Machine Learning: Classification

por Paul A

•

6 de feb. de 2021

Overall, an excellent course. It gives a great introduction to many of modern and old machine learning models, and a brief glimpse in dealing with unbalanced data; a subject you can freely explore on your own. The strongest part of this course are the guided demos, they are excellent to see things happen in real time, with many ah-ha! moments, and filled code you can adapt to other projects.

However, there's a catch; to me, a big one. The guided demos; although excellent, are flawed. If you follow the practices presented in the demo, you generate a lot of data leakage into the predictions. Specially when doing cross validation with gridsearch, since the training is not done with a pipeline. Be careful when implementing your own machine learning models after following this course.

por Fitrie R

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23 de dic. de 2020

This course is a next level after understanding classification machine learning model. All my questions had been answered with this module. The instructor is very great to clarify the whole python code used. Highly recommended course

por Ashish P

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1 de mar. de 2021

Superb ,detailed, well explained, lots of hands on training through labs and most of the major alogrithms are covered!

Keep up the good work. You guys are helping the community a lot :D

por Abdillah F

•

8 de nov. de 2020

Great course and very well structured. I'm really impressed with the instructor who give thorough walkthrough to the code.

por Volodymyr

•

28 de jul. de 2021

Very good material and approach to Human Learning +5 :)

por Hossam M

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22 de ago. de 2021

The course content is very great in the coding area and it is very helping. but a shortage that is clear is the theory behind every algorithm, the handling of it wasn't that much perfect.

por SMRUTI R D

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27 de ago. de 2021

It is an excellent course on Classification. The approach of the course is different from similar courses I had attended earlier. It presents different classification algorithms as a continuous whole with increasing degree of sophistication rather as disjoint ones. This helped in understanding the entire range of available options and how to apply them in different situations. The faculty was very clear and precise in his presentations. Many thanks to IBM / Coursera.

por Willber d S N

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25 de ene. de 2023

One of the best data science courses on the platform. It has theory and a lot of practical content. Also, learn a number of classification models and how to deal with some of their problems. I recommend this course. I am very grateful to the teachers and the entire team that prepared this material of such high quality. Thank you very much.

por Pulkit K

•

1 de oct. de 2021

Excellent course . I have done a lot of data science courses on Coursera and this one by far is the most comprehensive course on this subject matter and the training examples in the notebook, all are very well explained. Highly recommend it to everyone.

por Nicola R

•

22 de feb. de 2022

Great course, well structured. The presentation of the different methods is very clear and well separated to understand the differences. A good understanding of classifiers is gained from this course.

por Adolfo D

•

6 de feb. de 2023

Well-structured learning path. If you dont have previous python experience you can catch up after a couple of weeks as the workflow is similar regardless of the algorithmn you are using

por Juan M

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18 de jun. de 2021

The course is very well structured, and the explanations very clear. I would only suggest enhancing the peer-review community since it takes a long time to get a review sometimes.

por Alparslan T

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7 de ene. de 2022

Excellent theoretical and practical understanding in classification algorithms. The instructor is really of a very high level and I appreciate his effort.

por Vallian S

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8 de ago. de 2022

It's a greate course. I learned a lot, from deeper understanding basic algorithms to more advanced technique such as bagging and model explanability.

por konutek

•

17 de dic. de 2020

The instructor from videos is amazing. Great tutor. So far the courses from IBM Machine Learning Professional Certificate are really, really good.

por Jose M

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19 de ene. de 2021

I would like to give especial thanks to the instructor (the one in the videos) for his great job. It would be nice to know who is is.

por Rafael A O

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29 de oct. de 2022

A wonderful experience... learnt a lot and understood the rol of EDA, the method to evaluate classifiers with different metrics...

por nico l

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26 de nov. de 2021

Super content and good practice, perfect if you want to get an overview of all ML classification algo including ensemble methods !

por Saraswati P

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23 de sep. de 2021

Well structured training. Lab sessions and assignments are well planned to get clarity on concepts and practical application.

por JV K

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15 de sep. de 2022

The course is well designed and easy to follow. (communication and feedback mechanism with Coursera could be improved).

por My B

•

19 de abr. de 2021

A well-structured and practical course which helps me answer lots of my concerns from the past until now.

por Ranjith P

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13 de abr. de 2021

I recommend this course to everyone who wants to excel in Machine Learning. This is a Great Course!

por Hariom S

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2 de oct. de 2021

It was a perfect experience and the instructor was very good. Thanks, IMB and Coursera

por Rorisang S

•

16 de may. de 2021

Fantastic presentations and detailed course material make this course really worth it!

por Paulo E B d M

•

8 de jun. de 2022

It took longer than I expected. Lots of information, but high quality and useful.