What Is TensorFlow and Why Is It So Popular?

TensorFlow is an open-source machine learning (ML) and deep learning framework developed by Google. It’s used to build, train, and deploy AI models—especially neural networks.

What Exactly Is TensorFlow?

At its core, TensorFlow is a software library used to create and train machine learning models. These models take data as input, learn patterns from it, and then use those patterns to make predictions or classifications.

TensorFlow works with tensors, which are multi-dimensional arrays (similar to vectors and matrices). Data flows through a sequence of mathematical operations, allowing the model to learn and improve over time—hence the name TensorFlow.

TensorFlow helps computers learn from data and make predictions or decisions, such as:

• Recognizing images or speech
• Translating languages
• Recommending products or videos
• Detecting fraud or anomalies

import tensorflow as tf

model = tf.keras.Sequential([
    tf.keras.layers.Dense(10, activation='relu'),
    tf.keras.layers.Dense(1)
])

model.compile(optimizer='adam', loss='mse')

TensorFlow vs PyTorch (quick comparison)

Who uses TensorFlow?

• Google
• Airbnb
• Twitter/X
• Uber
• Many startups and research teams
• When should you use TensorFlow?

Use TensorFlow if you want to:

• Build production-grade ML systems
• Deploy models to mobile, web, or cloud
• Work with large-scale data or models