TensorFlow Tutorial

Welcome to the TensorFlow tutorial! TensorFlow is an open-source software library for dataflow programming across a range of tasks. It is widely used for machine learning and deep learning applications.

Install TensorFlow

Before you start, make sure you have TensorFlow installed. You can install it using pip:

pip install tensorflow

Basic Concepts

Tensor: A tensor is a generalization of vectors and matrices. It can be used to represent a wide range of data structures.
Graph: A TensorFlow program is represented as a graph. The graph consists of nodes and edges. Nodes represent operations and edges represent the flow of data between operations.
Session: A session is used to execute the operations in the graph.

Example

Here's a simple example of a TensorFlow program:

import tensorflow as tf

# Create a constant tensor
a = tf.constant([[1, 2], [3, 4]])

# Create a matrix multiplication operation
b = tf.matmul(a, a)

# Start a TensorFlow session
with tf.Session() as sess:
    # Run the matrix multiplication operation
    result = sess.run(b)
    print(result)

More Resources

For more detailed information, please check out the official TensorFlow documentation: TensorFlow Documentation.