Update README.md

[PoorvaTi]

from keras.models import Sequential
from keras.layers import Reshape, Conv2D, MaxPooling2D, Flatten, Dense, Dropout

Assuming you've loaded and preprocessed your data (X, y)

Create a Sequential model

model = Sequential()

Reshape input to (40, 1, 1)

model.add(Reshape((40, 1, 1), input_shape=(40, 1)))

Convolutional layers

model.add(Conv2D(32, kernel_size=(3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

model.add(Conv2D(64, kernel_size=(3, 3), activation='relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

Flatten layer

model.add(Flatten())

Dense layers

model.add(Dense(128, activation='relu'))
model.add(Dropout(0.2))

model.add(Dense(64, activation='relu'))
model.add(Dropout(0.2))

Output layer

model.add(Dense(7, activation='softmax'))

Compile the model

model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])

Print model summary

model.summary()