TensorFlow and Keras Explained

TensorFlow and Keras are two of the most widely used tools for building and training deep learning models in Python.

What TensorFlow Is

TensorFlow is an open source library developed by Google, designed to handle the heavy mathematical computations involved in training neural networks, including support for running models efficiently on GPUs.

What Keras Is

Keras is a higher level interface that runs on top of TensorFlow, allowing developers to build neural networks using simple, readable code, without manually handling low level computation details.

Building a Simple Model

from tensorflow import keras

model = keras.Sequential([
    keras.layers.Dense(16, activation="relu"),
    keras.layers.Dense(1, activation="sigmoid")
])

model.compile(optimizer="adam", loss="binary_crossentropy")

Why This Combination Is Popular

Keras makes model building beginner friendly, while TensorFlow handles performance and scalability, which is why this combination is widely used across both research and production systems.