Book Image

Deep Learning Using Keras - A Complete and Compact Guide for Beginners [Video]

By : Abhilash Nelson
5 (1)
Book Image

Deep Learning Using Keras - A Complete and Compact Guide for Beginners [Video]

5 (1)
By: Abhilash Nelson

Overview of this book

The artificial intelligence domain is divided broadly into deep learning and machine learning. In fact, deep learning is machine learning itself but deep learning with its deep neural networks and algorithms tries to learn high-level features from data without human intervention. That makes deep learning the base of all future self-intelligent systems. This course begins with going over the basics of Python and then quickly moves on to important libraries of Python that are critical to data analysis and visualizations, such as NumPy, Pandas, and Matplotlib. After the basics, we will then install the deep learning libraries—Theano and TensorFlow—and the API for dealing with these called Keras. Then, before we jump into deep learning, we will have an elaborate theory session about the basic structure of artificial neuron and neural networks, and about activation functions, loss functions, and optimizers. Furthermore, we will create deep learning multi-layer neural network models for a text-based dataset and then convolutional neural networks for an image-based dataset. You will also learn how the basic CNN layers such as the convolution layer, the pooling layer, and the fully connected layer work. Then, we will use different techniques to improve the quality of a model and perform optimization using image augmentation. By the end of this course, you will have a complete understanding of deep learning and will be able to implement these skills in your own projects. The complete code bundle for this course is available at https://github.com/PacktPublishing/Deep-Learning-using-Keras---A-Complete-and-Compact-Guide-for-Beginners
Table of Contents (29 chapters)
Free Chapter
1
Course Introduction
3
Setting Up Computer
8
Installing Libraries
9
Artificial Neuron and Neural Network
10
Activation Functions
11
Popular Activation Functions
12
Popular Types of Loss Functions
13
Popular Types of Optimizers
14
Popular Neural Network Types
22
Transfer Learning Using Pretrained Models
24
ResNet50
25
Transfer Learning Training Flowers Dataset
26
Transfer Learning Flower Prediction
27
VGG16 Transfer Learning Using Google Colab GPU
28
VGG19 Transfer Learning using Google Colab GPU
29
ResNet-50 Transfer Learning using Google Colab GPU
Chapter 18
Digital Image Basics
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Section 1
Digital Image
In this video, let us understand some basics of digital image.