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Avis et commentaires pour d'étudiants pour Simple Recurrent Neural Network with Keras par Coursera Project Network

4.5
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98 évaluations
14 avis

À propos du cours

In this hands-on project, you will use Keras with TensorFlow as its backend to create a recurrent neural network model and train it to learn to perform addition of simple equations given in string format. You will learn to create synthetic data for this problem as well. By the end of this 2-hour long project, you will have created, trained, and evaluated a sequence to sequence RNN model in Keras. Computers are already pretty good at math, so this may seem like a trivial problem, but it’s not! We will give the model string data rather than numeric data to work with. This means that the model needs to infer the meaning of various characters from a sequence of text input and then learn addition from the given data. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with Python, Jupyter, and Tensorflow pre-installed. Please note that you will need some experience in Python programming, and a theoretical understanding of Neural Networks to be able to finish this project successfully. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions....

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1 - 14 sur 14 Avis pour Simple Recurrent Neural Network with Keras

par Pravin S

May 22, 2020

Best Understanding of Recurrent Neural Network in simplest way.

par SENTHIL K B

May 12, 2020

Excellent planning and guidance throughout

par Gangone R

Jul 04, 2020

very useful course

par Prakash S

May 31, 2020

Excellent tool

par Kamlesh C

Jun 21, 2020

Thanks

par Abel F Z C

Jul 09, 2020

good

par Vajinepalli s s

Jun 20, 2020

nice

par Ashwin P

May 12, 2020

good

par Daniel S R

Jul 13, 2020

Good guided course. I would add a quite more deep details in the model architecture to understand better how are the inputs and the outputs of each layer in the RNN model

par Mohammed B

Jun 25, 2020

good

par Mónika J

May 13, 2020

I think that the explanation on the code is not enough for beginners and that it mostly depends on the student's background and effort wether they understand it or not.

par Salil M

May 22, 2020

The knowledge about RNN was average, it was mainly focusing on data processing for RNN use, can be improved by using RNN more rigorously

par Pramod H K

Jul 26, 2020

Very good and simple intro to RNN.

par Dr R S

May 11, 2020

Will learn the PYTHON soon and get expert in this.