The Learning of Deep Learning: Overview, Methods, and Applications
-
R Regan
Abstract
An extraordinary self-driving car was introduced onto the busy roads of United States America a few years ago. The look of the vehicle is like all other tonomous cars demonstrated by Tesla, General Motors, or Google, but the magic of artificial intelligence (AI) was introduced in it. The car was designed in such a way that it would not follow any instruction of an engineer or programmer. But, the function of the car was taught by itself by an algorithm that was designed by watching how a human driver would do. Getting a car that performs all the functions with the magic of AI is a remarkable achievement. But it is not absolutely understandable the way the car makes its decisions. The information is received from the car’s sensors and the received information has been passed directly into a huge network of artificial neurons to perform certain functions by processing the data. The response gives the impression as it would come from the human driver. That is, the magical show of AI. With AI and deep learning, it is made possible to ask questions to a machine and get answers about stock, customer relation, sales, fault detection, and much more. The computer can also determine to provide relevant information that is actually asked. AI provides a brief summary of the data and suggests the possible ways to analyze it. In health care field, a firm decision is taken on the efficiency of the treatment and plug-in or supplementary items are easily recommended at a greater rate in retail applications. In finance department, fault can be stopped from happening instead of just getting attention. In above exemplified applications, the physical system easily recognizes the needed information, tries to find the relationships among the used variables, and formulates an answer. Once the answer is formulated, the system will automatically communicate with options for follow-up queries.
Abstract
An extraordinary self-driving car was introduced onto the busy roads of United States America a few years ago. The look of the vehicle is like all other tonomous cars demonstrated by Tesla, General Motors, or Google, but the magic of artificial intelligence (AI) was introduced in it. The car was designed in such a way that it would not follow any instruction of an engineer or programmer. But, the function of the car was taught by itself by an algorithm that was designed by watching how a human driver would do. Getting a car that performs all the functions with the magic of AI is a remarkable achievement. But it is not absolutely understandable the way the car makes its decisions. The information is received from the car’s sensors and the received information has been passed directly into a huge network of artificial neurons to perform certain functions by processing the data. The response gives the impression as it would come from the human driver. That is, the magical show of AI. With AI and deep learning, it is made possible to ask questions to a machine and get answers about stock, customer relation, sales, fault detection, and much more. The computer can also determine to provide relevant information that is actually asked. AI provides a brief summary of the data and suggests the possible ways to analyze it. In health care field, a firm decision is taken on the efficiency of the treatment and plug-in or supplementary items are easily recommended at a greater rate in retail applications. In finance department, fault can be stopped from happening instead of just getting attention. In above exemplified applications, the physical system easily recognizes the needed information, tries to find the relationships among the used variables, and formulates an answer. Once the answer is formulated, the system will automatically communicate with options for follow-up queries.
Chapters in this book
- Frontmatter I
- Contents V
- List of Authors VII
- The Learning of Deep Learning: Overview, Methods, and Applications 1
- Foundation of Cognitive Computing 19
- Applications and Implications of Artificial Intelligence and Deep Learning in Computer Vision 35
- A Study of Voice Recognition System Using Deep Learning Techniques 53
- Building Machine Learning–Based Prediction System for Critical Diseases 75
- An Overview of Internet of Things and Machine Learning for Smart Healthcare 97
- Nutrition Food Recognition Using Deep Learning Algorithm for Physically Challenged Human Being 113
- Healthcare Data Analysis Using Deep Learning Paradigm 129
- Cognitive Authentication for Smart Healthcare System 149
- Cognitive-Inspired Computer Vision Assist System for Diabetic Retinopathy Detection from Fundus Images 165
- A Novel Deep Belief Neural Network Model for Abstractive Text Summarization 179
- Index 201
Chapters in this book
- Frontmatter I
- Contents V
- List of Authors VII
- The Learning of Deep Learning: Overview, Methods, and Applications 1
- Foundation of Cognitive Computing 19
- Applications and Implications of Artificial Intelligence and Deep Learning in Computer Vision 35
- A Study of Voice Recognition System Using Deep Learning Techniques 53
- Building Machine Learning–Based Prediction System for Critical Diseases 75
- An Overview of Internet of Things and Machine Learning for Smart Healthcare 97
- Nutrition Food Recognition Using Deep Learning Algorithm for Physically Challenged Human Being 113
- Healthcare Data Analysis Using Deep Learning Paradigm 129
- Cognitive Authentication for Smart Healthcare System 149
- Cognitive-Inspired Computer Vision Assist System for Diabetic Retinopathy Detection from Fundus Images 165
- A Novel Deep Belief Neural Network Model for Abstractive Text Summarization 179
- Index 201
