the very first commit mssage

.gitignore

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+venv

README.md

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+```
+pip install numpy tensorflow
+```
+
+`main.py` didnt run due to `NumPy` import issue. The error is given below :
+```
+Traceback (most recent call last):
+  File "/home/hdmtp/Image_recog/venv/lib/python3.10/site-packages/numpy/core/__init__.py", line 23, in <module>
+    from . import multiarray
+  File "/home/hdmtp/Image_recog/venv/lib/python3.10/site-packages/numpy/core/multiarray.py", line 10, in <module>
+    from . import overrides
+  File "/home/hdmtp/Image_recog/venv/lib/python3.10/site-packages/numpy/core/overrides.py", line 6, in <module>
+    from numpy.core._multiarray_umath import (
+ImportError: libz.so.1: cannot open shared object file: No such file or directory
+
+During handling of the above exception, another exception occurred:
+
+Traceback (most recent call last):
+  File "/home/hdmtp/Image_recog/main.py", line 1, in <module>
+    import numpy as np
+  File "/home/hdmtp/Image_recog/venv/lib/python3.10/site-packages/numpy/__init__.py", line 141, in <module>
+    from . import core
+  File "/home/hdmtp/Image_recog/venv/lib/python3.10/site-packages/numpy/core/__init__.py", line 49, in <module>
+    raise ImportError(msg)
+ImportError: 
+
+IMPORTANT: PLEASE READ THIS FOR ADVICE ON HOW TO SOLVE THIS ISSUE!
+
+Importing the numpy C-extensions failed. This error can happen for
+many reasons, often due to issues with your setup or how NumPy was
+installed.
+
+We have compiled some common reasons and troubleshooting tips at:
+
+    https://numpy.org/devdocs/user/troubleshooting-importerror.html
+
+Please note and check the following:
+
+  * The Python version is: Python3.10 from "/home/hdmtp/Image_recog/venv/bin/python3"
+  * The NumPy version is: "1.24.2"
+
+and make sure that they are the versions you expect.
+Please carefully study the documentation linked above for further help.
+
+Original error was: libz.so.1: cannot open shared object file: No such file or directory
+```

main.py

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+import numpy as np
+from tensorflow import keras
+from keras.constraints import maxnorm
+from keras.utils import np_utils
+
+seed = 21
+
+from keras.datasets import cifar10
+'''
+The CIFAR-10 dataset 
+(Canadian Institute for Advanced Research, 10 classes) 
+is a subset of the Tiny Images dataset and 
+consists of 60000 32x32 color images.
+'''
+
+# loading the data
+(x_train, y_train), (x_test, y_test) = cifar10.load_data()
+
+#Normalize the inputs from 0-255 to between 0 and 1 by dividing by 255
+x_train = x_train.astype('float32')
+x_test = x_test.astype('float32')
+x_train = x_train/255.0
+x_test = x_test/255.0
+
+# One-hot encode outputs
+'''
+Another thing we'll need to do to get the data ready for the network is to one-hot encode the values. 
+Lets not go into the specifics of one-hot encoding here, but for now know that the images can't be used by the network as they are, 
+they need to be encoded first and 
+one-hot encoding is best used when doing binary classification.
+'''
+y_train = np_utils.to_categorical(y_train)
+y_test = np_utils.to_categorical(y_test)
+class_num = y_test.shape[1]
+
+
+model = keras.Sequential()
+model.add(keras.layers.layer1)
+model.add(keras.layers.layer2)
+model.add(keras.layers.layer3)
+
+model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy', 'val_accuracy'])
+
+print(model.summary())