How do I train a model using Keras?

How do I train a model using Keras?

To train a model in Keras, you first need to define your model architecture, compile it, and then fit it to your data.

What kind of data do I need to train a model?

You typically need labeled data for supervised learning, which includes input features and corresponding target labels.

Can you show me a simple code example?

Sure! Here's a basic example:

from keras.models import Sequential
from keras.layers import Dense

model = Sequential()
model.add(Dense(32, activation='relu', input_shape=(input_dim,)))
model.add(Dense(1, activation='sigmoid'))

model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
model.fit(X_train, y_train, epochs=10, batch_size=32)

What should I do if my model is overfitting?

You can try techniques like adding dropout layers, using regularization, or gathering more training data.