From where should we import training data in deeplearning

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From where should we import training data in deeplearning

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One way is to use preloaded datasets

from tensorflow.keras.datasets import mnist
(mnist_train_images, mnist_train_labels), (mnist_test_images, mnist_test_labels) = mnist.load_data()

There are many othweways which involves reading data from numpy arrays, pandas dataframes,labelled images etc

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Here is the documentation for loading a pandas dataframe as a tensorflow dataset
https://www.tensorflow.org/tutorials/load_data/pandas_dataframe

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How do we import data from labelled images?

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Hi @rupasri_achanta
Please elaborate your query more clearly. From where you want to download the images? What did you try to do? How are those images labeled? things like these.
Thanks!

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Hi @manish_kc_06. .This is my query can you help me in it?

I had a data with labelled images of cat and not cat .I wanna load that data and predict an unknown image whether it is a cat or not and as I’m a beginner in deeplearning I was predicting it not by using tensorflow and I’m using numpy and all that activation functions and I was told that by importing following modules I can do that project:

import numpy as np
import matplotlib.pyplot as plt
import h5py
import scipy
from PIL import image from Scipy import ndimage
from lr_utils import load_dataset
%matplotlib inline

And I didn’t understand what lr_utils module will do I searched for it in google but I didn’t get it what it will do and I decided to find an alternative to that module so that I can run that project.

AND lr_utils IS USED TO LOAD DATASET AND THIS PROJECT IS IN COURSERA AND THE NEXT STEP IS

To load dataset :

train_set_x_orig,train_set_y,test_set_x_orig, test_set_y,classes=load_dataset()

We can plot the pictures of cat by
index=5
plt.imshow(train_set_x_orig[index])
print(“y=”+str(train_set_y[:,index])+",it’s a "+classes[np.squeeze(train_set_y[:,index])].decode(“utf-8”)+“picture”