NumPy - Python Library for Matrix operations

This section provides a tutorial example on how to install Python 3 NumPy library on macOS computers. NumPy is widely used by Python users for matrix operations required in neural network models.

What Is NumPy? NumPy is an open-source Python library for matrix operations developed initially by Travis Oliphant and now maintained by the NumPy community.

If you want to build neural network models in Python, you should install NumPy and get familiar with its functionalities by following this tutorial. This is because neural network models require lots of matrix operations, which are provided in NumPy.

1. Make sure you have python 3 installed by running the "python3" command in a terminal window:

herong$ python3 --version

Python 3.8.0

2. Install NumPy library using the "pip3" (Package Installer for Python 3) command:

herong$ sudo pip3 install numpy

Collecting numpy
  Downloading https://files.pythonhosted.org/packages/...
Installing collected packages: numpy
Successfully installed numpy-1.19.0

3. Verify NumPy installation by importing "numpy" package, retrieving its version string, and creating a 3x4 matrix of random numbers:

herong$ python3
Python 3.8.0 (v3.8.0:fa919fdf25, Oct 14 2019, 10:23:27)

>>> import numpy as np

>>> np.1.20
'1.19.0'

>>> np.random.rand(3,4)
array([[0.98825753, 0.73001974, 0.01652119, 0.12592153],
     [0.44776361, 0.36145535, 0.380565  , 0.32035704],
     [0.61031541, 0.5521491 , 0.70684916, 0.05019113]])

Cool! You have NumPy library ready on your Python 3 environment for matrix operations.

For more readings on NumPy, visit NumPy documentation Website at https://numpy.org/doc/.

Table of Contents

 About This Book

 Deep Playground for Classical Neural Networks

Building Neural Networks with Python

 Python Environment on macOS

NumPy - Python Library for Matrix operations

 SciPy - Python Library for Mathematical Functions

 Simple Example of Neural Networks

 TensorFlow - Machine Learning Platform

 PyTorch - Machine Learning Platform

 CNN (Convolutional Neural Network)

 RNN (Recurrent Neural Network)

 GNN (Graph Neural Network)

 References

 Full Version in PDF/EPUB