Publisher's Synopsis
Different computer concepts have been misused and sometimes interchanged, leading to confusion, especially for new computer users and researchers. However, the knowledge of computer studies terms these concepts, which are almost similar but differ from each other. Besides, all these concepts of computer systems, both hardware and software are connected or depend on each other in different ways. As such, this book is what you have been waiting for to learn these terms, which seem to represent a similar computer process.
The metrics of how broad computer studies do not matter, but the primary understanding of these concepts does. Machine learning, data science, pattern recognition, artificial intelligence, and deep learning are the most commonly confused and interchanged terms used out there. Inside this book, however, you will find the descriptions of both machine learning and data science and their connections and relationship. That is, you have to initially learn and have a general idea about machine learning and data science, which therefore provides a connection between the two concepts. Inside, you will find an overview of machine learning, including the definition, building blocks, and the common types used today.
On the other hand, you will also find all you need to know about data science, including the definition and a general understanding through highlighted examples. Besides, the book also details the components of data science, allowing you to note the differences and similarities with machine learning. To this end, you will then find the connection between machine learning and data science, including the similarities which confuse some individuals and the differences, which separates these two computer study concepts. Also, inside, you will find the impact of neural networks on both machine learning and pattern recognition.
The book initially details about neural networks, which is an essential topic in computer studies, especially in making machines learn, think, and behave like humans. You will find a general overview of neural networks and how the human brain structure and functions contributed to the creation of learning skills in computers. Also included are the components of neural networks and the connection it has to machine learning. Neural networks provide a significant contribution to machine learning, especially in handling complex datasets. Similarly, also included in the book is the contribution of neural networks in pattern recognition. Pattern recognition is another essential form of intelligence in machines where arrangements and retrieval of information based on trends are made possible by neural networks.
Inside You Will Find
- The general understanding of machine learning, data science, neural networks, and pattern recognition
- The components of machine learning, data science, and neural networks
- Essential types of machine learning and how they help in the creation of information used in other computer concepts
- Similarities and differences between machine learning and data science
- The connection and relationship between data science and machine learning especially when it comes to the facilitation of processes datasets analysis
- Neural networks in machine learning and how they learn new information
- Neural networks in pattern recognition as well as its benefits in distinguishing different shapes, objects and images
- And more...
