Book Image

Neural Network Projects with Python

By : James Loy
Book Image

Neural Network Projects with Python

By: James Loy

Overview of this book

Neural networks are at the core of recent AI advances, providing some of the best resolutions to many real-world problems, including image recognition, medical diagnosis, text analysis, and more. This book goes through some basic neural network and deep learning concepts, as well as some popular libraries in Python for implementing them. It contains practical demonstrations of neural networks in domains such as fare prediction, image classification, sentiment analysis, and more. In each case, the book provides a problem statement, the specific neural network architecture required to tackle that problem, the reasoning behind the algorithm used, and the associated Python code to implement the solution from scratch. In the process, you will gain hands-on experience with using popular Python libraries such as Keras to build and train your own neural networks from scratch. By the end of this book, you will have mastered the different neural network architectures and created cutting-edge AI projects in Python that will immediately strengthen your machine learning portfolio.
Table of Contents (10 chapters)

The cats and dogs dataset

Now that we understand the theory behind CNNs, let's dive into data exploration. The cats and dogs dataset is provided by Microsoft. The instructions for the downloading and setting up of the dataset can be found in the Technical requirements section of this chapter.

Let's plot the images to better understand the kind of data we're working with. To do that, we can simply run the following code:

from matplotlib import pyplot as plt
import os
import random

# Get list of file names
_, _, cat_images = next(os.walk('Dataset/PetImages/Cat'))

# Prepare a 3x3 plot (total of 9 images)
fig, ax = plt.subplots(3,3, figsize=(20,10))

# Randomly select and plot an image
for idx, img in enumerate(random.sample(cat_images, 9)):
img_read = plt.imread('Dataset/PetImages/Cat/'+img)
ax[int(idx/3), idx%3].imshow(img_read)
ax[int(idx/3),...