Book Image

Deep Learning By Example

Book Image

Deep Learning By Example

Overview of this book

Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence.
Table of Contents (18 chapters)
16
Implementing Fish Recognition

Logistic regression model – building and training

Also based on our explanation of logistic regression in Chapter 2, Data Modeling in Action - The Titanic Example, we are going to implement the logistic regression algorithm in TensorFlow. So, briefly, logistic regression passes the input through the logistic/sigmoid but then treats the result as a probability:

Figure 13: Discriminating between two linearly separable classes, 0's and 1's

Utilizing logistic regression in TensorFlow

For us to utilize logistic regression in TensorFlow, we first need to import whatever libraries we are going to use. To do so, you can run this code cell:

import tensorflow as tf

import pandas as pd

import numpy as np
import time
from...