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Volver a Introduction to Deep Learning & Neural Networks with Keras

Opiniones y comentarios de aprendices correspondientes a Introduction to Deep Learning & Neural Networks with Keras por parte de Habilidades en redes de IBM

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Acerca del Curso

Looking to start a career in Deep Learning? Look no further. This course will introduce you to the field of deep learning and help you answer many questions that people are asking nowadays, like what is deep learning, and how do deep learning models compare to artificial neural networks? You will learn about the different deep learning models and build your first deep learning model using the Keras library. After completing this course, learners will be able to: • Describe what a neural network is, what a deep learning model is, and the difference between them. • Demonstrate an understanding of unsupervised deep learning models such as autoencoders and restricted Boltzmann machines. • Demonstrate an understanding of supervised deep learning models such as convolutional neural networks and recurrent networks. • Build deep learning models and networks using the Keras library....

Principales reseñas

MP

30 de jun. de 2022

Excellent introduction to the mechanics of Neural Networks in general, and the Keras application specifically. Alec is an outstanding teacher, I always appreciate his knowledge and enthusiasm.

AB

15 de mar. de 2020

Interesting course. Forward propagation, gradient descent, backward propagation, the vanishing gradient problem, (+ Regression, Classification, and CNN with Keras) explained clearly.

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151 - 175 de 225 revisiones para Introduction to Deep Learning & Neural Networks with Keras

por MD. S I

23 de ago. de 2020

A great course.

por RuoxinLi

9 de nov. de 2019

exellent course

por Edson J M

17 de ago. de 2020

perfect course

por Julien V

3 de jun. de 2020

Great course !

por Gabriela A N

29 de ago. de 2021

Great classes

por Pedro G D

6 de ago. de 2021

Its fantastic

por Mitchell H

27 de jun. de 2020

Great Course!

por Branly F L

14 de may. de 2020

Very nice..!!

por Abdullaev S

29 de mar. de 2021

Very helpful

por Sunny D

26 de mar. de 2020

Really nice!

por Sima Q

29 de jul. de 2021

V​ery Good!

por Muhammad J B

27 de jul. de 2021

Just great!

por THOMONT B

10 de ene. de 2021

Nice course

por Aditya M P

2 de dic. de 2020

Good Course

por Abul B

10 de mar. de 2022

Excellent

por Sambit S

1 de sep. de 2021

very good

por Dr C S Y

22 de ago. de 2021

Excellent

por Souvik M

21 de abr. de 2020

Excellent

por Saman S

25 de sep. de 2019

wonderful

por Ridha O

11 de feb. de 2022

good one

por Francisco M L L

8 de ago. de 2022

great

por said f

29 de mar. de 2020

super

por Krishna H

29 de abr. de 2020

good

por Rafael G

3 de nov. de 2021

Very good course which gives a good introduction to the field. Don't get intimidated by the math you will see and make sure you understand the workflow. Once you do that you will basically repeat it in which one of the neural network types presented at the course. In a negative not, I missed the intructor elaboring how to identity problems that could be approached by applying DL. But I complemented studies on other documents in the internet and that's ok.

por Michael M

14 de abr. de 2020

It was a pretty good brief, rapid intro. I frankly was expecting more content on options and explanations, but it covered the very essential basics. The final exercise did ask for students to use tools not gone over in class (a bit of scikit-learn). Since I've used scikit-learn before, this wasn't hard for me, but it may be for a newcomer, and actually isn't needed to meet the goals of the assignment, so I'm not sure why it was there.