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Avis et commentaires pour d'étudiants pour Introduction to Deep Learning & Neural Networks with Keras par IBM

4.7
étoiles
912 évaluations
186 avis

À propos du cours

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....

Meilleurs avis

AB
15 mars 2020

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

AM
24 juin 2020

Good course. It is a very direct approach. It is a basic introduction to keras. Doing the labs is recommended, and also previous knowledge about machine learning is encouraged.

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126 - 150 sur 187 Avis pour Introduction to Deep Learning & Neural Networks with Keras

par Julien V

3 juin 2020

Great course !

par Gabriela A N

29 août 2021

Great classes

par Pedro G D

6 août 2021

Its fantastic

par Mitchell H

27 juin 2020

Great Course!

par Branly L

14 mai 2020

Very nice..!!

par Abdullaev S

29 mars 2021

Very helpful

par Sunny D

26 mars 2020

Really nice!

par Sima Q

29 juil. 2021

V​ery Good!

par Muhammad J B

27 juil. 2021

Just great!

par THOMONT B

10 janv. 2021

Nice course

par Aditya M P

2 déc. 2020

Good Course

par Sambit S

1 sept. 2021

very good

par Dr C S Y

22 août 2021

Excellent

par Souvik M

21 avr. 2020

Excellent

par Saman S

25 sept. 2019

wonderful

par said f

29 mars 2020

super

par Krishna H

29 avr. 2020

good

par Michael M

14 avr. 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.

par Xiaoer H

30 juin 2020

The course contents are not in-depth enough. The server for Jupyter notebook running is way too slow. Besides, the peer review homework is not that good, because some people didn't read through the questions carefully enough, and they misunderstood the questions themselves and could not give fair enough grades to peers. If the final assignment can be made to auto-grading one, it would be much better (we can set the same random seed)

par lonnie

15 juin 2021

I​ have experience of Deep Learning, so I am able to walk through this Lession quickly. The main focus is on Capstone Project, and I have learned something on it. To be honest, this lession is very elementary. I suggest to introduce more Deep Learning models and approachs in this lesson.

par Sander v d O

14 mars 2020

This is a great course. The lectures are boiled down to the essence of neural networks using Keras. I give four stars instead of five stars, because the IBM labs environment that the course uses was quite slow and buggy, so I ended up doing the exercises in Google Colab.

par Adriano S

23 oct. 2020

The Course is basic but interesting. I missed an exercise on backpropagation with the same explanatory level that it had for forward propagation. The last activity needs to be reviewed because it is confusing.

par Aaqib W S

20 mars 2020

A good course. Could be better if it was explained how to select the optimal number of layers and nodes. This was not covered and explained anywhere. Overall it was good.

par Rohit S

21 févr. 2020

I took this course for understanding the TensorFlow properly. Now I am in the situation to understand all the frameworks. Thanks a lot for providing me this free course

par Benhur O

10 oct. 2019

Good practical examples for ANN. It could be improved the theoretical part and compare better the architecture of the networks with the algorithms and code for Keras