Publisher's Synopsis
Are you need to learn rapidly Machine Learning?
This book is for you!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. The fear nestles on the insecurities that people have concerning survival, and this concern raises some 'what if' questions. What if machines became more intelligent than human beings and decided to eliminate any human being who was not as 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. When you come across any research on job automation, you should read it with a slight level of skepticism since the future of artificial intelligence and machines is unknown. Although technology is moving fast, its adoption is an unchartered path with unforeseen challenges. 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, which are the tasks that machine-learning engineers and data scientists.
