Recurrent Neural Networks (LSTM / RNN) Implementation with Keras - Python

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#RNN #LSTM #RecurrentNeuralNetworks #Keras #Python #DeepLearning

In this tutorial, we implement Recurrent Neural Networks with LSTM as example with keras and Tensorflow backend. The same procedure can be followed for a Simple RNN.

We implement Multi layer RNN, visualize the convergence and results. We then implement for variable sized inputs.

Recurrent Neural Networks RNN / LSTM / GRU are a very popular type of Neural Networks which captures features from time series or sequential data. It has amazing results with text and even Image Captioning.

In this example we try to predict the next digit given a sequence of digits. Same concept can be extended to text images and even music.

Find the codes here
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Best and easiest to understand LSTM implementation on Youtube. Loved how you show things not working at first and then you trying different solutions to make the model learn.

superaluis
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The best LSTM example in Youtube, thanks a lot

honestcommenter
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That small part in the end, how to train for different lengths of input sequence, that small part that is happiness. God bless bro

raghuwanshraj
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Welcome to the semicolon, where we'll be using Python...

cubicinfinity
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You have solved a big problem of mine that took me whole 2 days to solve, thank you man,
may god bless you

shobhitsrivastava
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It was pleasure watching out this video. You are doing really GREAT

pranavraj
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Excellent work, congrats. and thanks.

edphi
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Tutorials like this makes you wanna do more and learn more :-)

tech-py
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So surprised to see the performance improvement by normalising the input. Thank you.

GongweiWang
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your channel is underrated
u're doing a pretty good job keep up :)

portgasdace
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Thanks bro, This is exactly what I was looking for.

unknownuser
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Thanks for the tutorial. Really helpful.

JuanFlores-kimh
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Thank you very much! Short and full of Information, without fancy or difficult stuff! Like IT!

mariustrollmann
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Good video.
If you add the activation it will make the learn fast without adding a new layer.
Example:
model.add(LSTM(1, activation='relu', batch_input_shape=(None, 5, 1), return_sequences=False))

rquintal
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so helpful to built my fist lstm model..thanks a lot

amitsahoo
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With such simple data and high epochs, there's a very good chance that you're over-fitting. You should try testing it with an input sequence it hasn't seen.

braelyn.b__
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thank you Semicolon, this helped a lot!

sebiderug
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U r typing very very speed good to see it😍

laxminarasimhaduggaraju
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Great video. Please make more video on keras.

ravikantitare
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good, its the best tutorial ive ever seen

haokunliu
welcome to shbcf.ru