High-Level API for Building Models

Keras is a user-friendly, high-level API built to simplify the process of defining, training, and evaluating deep learning models. It abstracts many low-level operations, allowing developers to focus on high-level model design. With Keras, models can be written in a more readable and modular way, often in just a few lines of code.

• Sequential API: The most common way of defining a model. It allows for a linear stack of layers to be built sequentially. It’s ideal for simple models.pythonCopy codefrom keras.models import Sequential from keras.layers import Dense model = Sequential() model.add(Dense(units=64, activation='relu', input_dim=100)) model.add(Dense(units=10, activation='softmax'))
• Functional API: This allows for more complex models with shared layers or models with multiple inputs and outputs.pythonCopy codefrom keras.layers import Input, Dense from keras.models import Model inputs = Input(shape=(100,)) x = Dense(64, activation='relu')(inputs) outputs = Dense(10, activation='softmax')(x) model = Model(inputs=inputs, outputs=outputs)