Welcome to the TensorFlow documentation page. TensorFlow is an open-source software library for dataflow and differentiable programming across a range of tasks. Below, you will find an overview of the key features and how to get started.
Key Features
- Ease of Use: TensorFlow provides a flexible and high-level API for building and training models.
- Scalability: It can be used at scale on both single machines and clusters of machines with hundreds of machines.
- Flexibility: TensorFlow can run on multiple platforms including CPU, GPU, and TPU.
Getting Started
To get started with TensorFlow, you need to install it on your machine. You can find detailed instructions on how to do this in the TensorFlow installation guide.
Quick Start
Here's a simple example of a TensorFlow program that adds two numbers:
import tensorflow as tf
# Create a graph.
a = tf.constant(5)
b = tf.constant(6)
c = a + b
# Launch the graph and retrieve the result.
with tf.Session() as sess:
print(sess.run(c))
This will output 11.
Further Reading
Images
TensorFlow is not just about numbers; it's also about making sense of data. Here's an image to represent the concept of neural networks:
By exploring TensorFlow, you'll unlock the potential of deep learning and data analysis. Happy learning!