Machine Learning: Concepts, Tools and Techniques

Thinking of learning more in Machine Learning? Then you have landed in the right place. The overall aim of this book is to explore and examine key concepts, methods and techniques used in the Machine Learning. Machines have come a long way since the Industrial Revolution. They have become a part of our lives. No matter where you go, you will always find a machine around you, but it is only over the last few years that we have understood and enhanced the capabilities of machines. Machines can now perform tasks that involve the simulation of cognition, which is a task that until recently only human beings could accomplish. Driving cars, judging competitions and beating professional chess players at their game are just a few examples of the compound tasks that machines are now capable of performing. The ever-growing capabilities of machines are instilling a sense of fear among observers. What if machines became more intelligent than human beings become and decided to eliminate any human being who was not so smart as them? What if they were able to procreate and produce offspring, like Rachael and Deckard from Blade Runner, who had capabilities that humans never imparted to machines? What if singularity, which is considered to be a myth, is true? The other fear that people have is the threat to job security. BBC had conducted an online survey, "Will a robot take my job?" and it was concluded that job titles like waiters/waitresses, chartered accountants, taxi drivers, bar workers, and receptionists would become automated by the year 2040. Machine learning is not as simple as turning a switch on and off. It is not an out-of-the-box solution either. Machines and statistical algorithms work in parallel with each other. This book will help you explore exactly what Machine learning is and will introduce the reader the concepts, techniques, application of Machine Learning Algorithm with the practical case studies and walk-through examples to practice. By the time you are done reading this book, you will have a complete understanding as to what Machine Learning is. Following are the important points discussed in this book: What is Machine Learning? Subjects Involved in Machine Learning Facts about Machine Learning Types of Machine Learning Machine Learning Techniques Top Six Real Life Applications of Machine Learning Glossary on Important Machine Learning terms And more The main purpose of this course is to provide the most fundamental knowledge on Machine Learning to the reader so that they can understand what the Deep Learning is all about. Book Objectives To have an appreciation for Machine Learning and an understanding of their fundamental principles. To have an elementary adeptness in a Machine Learning Concepts and terms which includes an ability to understand the algorithms. To have an elementary understanding of (some of the) more advanced topics of Machine Learning such as Deep Learning and Support Vector Machine. Target Users This book designed for a variety of target audiences. The most suitable users would include: Newbies in Computer Science Techniques and Artificial Intelligence Professionals in Data scientist and Social Sciences Professors, lecturers, or tutors to be in position to find better ways to explain the content to their students with simples and easiest way The students and Academicians, especially those that are focusing on Machine Learning as their professions Scroll to the top and click on 'buy now' to get started.