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Opiniones y comentarios de aprendices correspondientes a AI Capstone Project with Deep Learning por parte de IBM

4.5
estrellas
390 calificaciones
69 reseña

Acerca del Curso

In this capstone, learners will apply their deep learning knowledge and expertise to a real world challenge. They will use a library of their choice to develop and test a deep learning model. They will load and pre-process data for a real problem, build the model and validate it. Learners will then present a project report to demonstrate the validity of their model and their proficiency in the field of Deep Learning. Learning Outcomes: • determine what kind of deep learning method to use in which situation • know how to build a deep learning model to solve a real problem • master the process of creating a deep learning pipeline • apply knowledge of deep learning to improve models using real data • demonstrate ability to present and communicate outcomes of deep learning projects...

Principales reseñas

RK

30 de jul. de 2020

The capstone of the project was really good it helped me to understand the deep learning concepts clearly for providing the solution.

RB

22 de may. de 2020

A very nice project based course to get hands on experience with deep learning\n\nand transfer learning.

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26 - 50 de 69 revisiones para AI Capstone Project with Deep Learning

por Branly F L

14 de may. de 2020

Excellent work from the teachers, thanks for your efforts.

por Nisar M

2 de sep. de 2020

Very good example to learn resnet pretrained models

por 林靖翰

31 de jul. de 2021

The teaching of this course is clear and complete

por shiva k P

13 de ene. de 2021

Great hands-on work of everything learnt so far!

por 011 S K

4 de abr. de 2020

Please labs are not so good. Please improve it.

por Anas O

13 de jun. de 2020

Thanks Dr. Alex, I always love your courses

por Carlo E C

21 de jul. de 2021

Real world approach to AI project

por Amine M B

9 de may. de 2020

Very interesting and helpful

por Morteza A

28 de oct. de 2021

very very good and helpful

por suprakash s

11 de may. de 2020

Excellent course!

por Krish g

3 de jun. de 2020

Marvelous course

por CHALLA K S N M S

23 de sep. de 2020

awesome course

por Julien V

3 de jun. de 2020

Great course !

por Christos

25 de feb. de 2020

Challenging!!

por Nanang K

25 de jul. de 2020

Noce project

por Shivam K

2 de feb. de 2022

Good course

por Yuanlong S

16 de feb. de 2021

good course

por Aditya M P

11 de dic. de 2020

Good Course

por TELAGARAPU P

18 de oct. de 2020

Good Course

por CARLOS S

26 de mar. de 2020

Thank you!

por THALLAM S G

9 de may. de 2022

excellent

por Alvaro B

6 de abr. de 2020

Excelent

por Claudia S

17 de may. de 2020

For the Keras part, it would be desirable if "clean" zip files were provided for week 2 to week 4 exercises, since they contain the MacOSX folder (which I think it is not required for the exercises). Also for Keras, it might be helpful if any other example could be found, since I do not think that using models which take that many hours (35 hours in Cognitive AI site / 8 hours in Google Colab) contribute in any way to the learning process. Or at least adjust them to use one epoch, like the Pytorch exercises

por Meenal I

16 de jul. de 2020

The course was good, but the only reason I gave it a 4* is because try as I might, the model fitting kept running out of memory on the provided system. I had to create an account on AWS to get my model to run. Maybe a consideration would be to try an alternate dataset that may fit in memory. I spent over 5 days trying it on IBM till before I had to move. to AWS. It was a great set of courses. Could have been a little more challenging as well.

por Julien P

19 de jun. de 2020

It's a great course to guide you through the full process of training a deep neural net. However, one needs to use external resources to train the model efficiently (Google Colab for example). The resources provided by IBM are not powerful enough to train the model in a reasonable amount of time (no GPU).