When Alan Turing, a computer science pioneer, replaced the question, ‘can machine think?’ with ‘can machines do what we can do?’ It was the turn of an era. The tussle between computer scientists began to devise computation techniques that mimic human thinking and pattern recognition.
We have come so far that artificial intelligence and machine learning helps us automate mundane and repetitive tasks saving organizations a lot of workforces, time, and money. If you’d like to learn more about computer science, please enroll in any ‘what is computer’ science course online. There are many options to choose from and at varying levels of knowledge.
Machine learning can be defined as studying algorithms that learn and evolve on their own. At the beginning of computer science, programs would do only basic computation and carry out tasks specifically coded to carry out. But today, high-level programming languages like python help developers build applications search engines that can observe consumer behavior, learn from it, and adapt themselves to emulate it.
There are a few ways that machine learning expedited the growth of computer science and has led to the emergence of new technologies. We discuss both here.
Processing Speed – Most technologically driven industries pile up massive amounts of data daily. This data has to be processed quickly and classified efficiently for information systems to be efficient. Machine learning has helped increase the processing speed of computation.
Real-time Analysis – Most databases and programming frameworks can now store and analyze data in a matter of seconds. They can perform predictive analysis to increase consumers’ conversion rates and prevent them from defecting to other brands. It helps businesses allocate their resources more efficiently and get the most out of their investments by identifying areas of improvement.
Proactive Design – Machine learning applications can find insights in large data sets. That also makes them capable of removing redundancies and repetitions. Since pattern recognition is an essential part of data analysis, processing speed and predictive analysis help businesses increase their revenue.
Growth of Deep Learning and Artificial Intelligence
Traditional machine learning applications have been surpassed by deep learning, but it was only possible because of how advanced machine learning became in the end. The overall machine learning market is projected to grow to $8.81 billion by 2022.
Deep learning is the future of artificial intelligence as it’s the most advanced computation method. Its models can perform time series analysis better than any other application. Deep learning neural networks are being developed to automate repetitive and mundane tasks that recognize patterns and make rational decisions.
There has been tremendous growth in machine learning, deep learning, and AI. Hence there is a lot of demand for professional expertise in these areas. Completing a machine learning online course can only stand to add value to your career in technology.