Removewat227indirgezginlerwin7 🤟🏻

Removewat227indirgezginlerwin7 🤟🏻

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Removewat227indirgezginlerwin7

A:

The issue here is that your tag is not a valid string because it has carriage returns. You have to convert your lines to a proper string:
for lines in tags.split(”
“):
tags += lines.split(”
“)

It is also strange that you are not using the ValueError.
If you are not using the ValueError you could just do this instead:
tags = []
for i in tags.split(”
“):
i = i.split(“,”)
tags.append(i)

Q:

LSTM, time series model, using fit_generator

I am trying to use Keras with Tensorflow 1.1.0 to make time series classification.
I have 10 features, 5 features are the features for each day, and 5 features are the features for each hour.
For the 1 time series, my first feature for each day is the total number of people at that location (considering 1 is the data we have for today)
And for the 2nd feature, I have the total number of people at that location for each hour.
I have the following data format:

I was trying to use fit_generator in Keras to predict new data, however, I am getting the following error
ValueError: setting an array element with a sequence.
During handling of the above exception, another exception occurred:

ValueError: Error when checking target: expected dense_4 to have 2 dimensions, but got array with shape (290, 2)
Here is the code for my model
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import LSTM
from keras.layers import TimeDistributed
from keras.layers import Activation

feature_dim = 10

features = [
[
[
1, 2, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,
1, 1, 1

https://colab.research.google.com/drive/13kh2XAH4ypj8uoY1-mYexzBUYS3ATkI-
https://colab.research.google.com/drive/1wufgkMn892SsVOw9U91xy5OsPwaIZEr5
https://colab.research.google.com/drive/1zSJ0l5YlEwVKgYCH6zkfIIpzntxki4D_
https://colab.research.google.com/drive/1p-olRplMy2Sq8d1YH62PjhmXTUBP-HrB
https://colab.research.google.com/drive/1I7fedtPndRRR3iho_l5CCOphgDs9dSbW

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