Book Image

TensorFlow 2.0 Quick Start Guide

By : Tony Holdroyd
Book Image

TensorFlow 2.0 Quick Start Guide

By: Tony Holdroyd

Overview of this book

TensorFlow is one of the most popular machine learning frameworks in Python. With this book, you will improve your knowledge of some of the latest TensorFlow features and will be able to perform supervised and unsupervised machine learning and also train neural networks. After giving you an overview of what's new in TensorFlow 2.0 Alpha, the book moves on to setting up your machine learning environment using the TensorFlow library. You will perform popular supervised machine learning tasks using techniques such as linear regression, logistic regression, and clustering. You will get familiar with unsupervised learning for autoencoder applications. The book will also show you how to train effective neural networks using straightforward examples in a variety of different domains. By the end of the book, you will have been exposed to a large variety of machine learning and neural network TensorFlow techniques.
Table of Contents (15 chapters)
Free Chapter
1
Section 1: Introduction to TensorFlow 2.00 Alpha
5
Section 2: Supervised and Unsupervised Learning in TensorFlow 2.00 Alpha
7
Unsupervised Learning Using TensorFlow 2
8
Section 3: Neural Network Applications of TensorFlow 2.00 Alpha
13
Converting from tf1.12 to tf2

Setting up the imports

To use this implementation with your own images, you need to save those images in the ./tmp/nst directory in your downloaded repository, then edit the content_path and style_path paths, shown in the following code.

As usual, the first thing we need to do is to import (and configure) the required modules:

import numpy as np
from PIL import Image
import time
import functools

import matplotlib.pyplot as plt
import matplotlib as mpl
# set things up for images display
mpl.rcParams['figure.figsize'] = (10,10)
mpl.rcParams['axes.grid'] = False

You may need to pip install pillow, which is a fork of PIL. Next comes the TensorFlow modules:

import tensorflow as tf

from tensorflow.keras.preprocessing import image as kp_image
from tensorflow.keras import models
from tensorflow.keras import losses
from tensorflow.keras import layers
from tensorflow.keras import...