Machine Learning Trends to Watch Out in 2021
The intersection between ML and IoT
The Internet of Things has become a fast-growing field recently. In 2030, the global IoT market will grow to 24.1 billion units, producing $1.5 trillion in revenue, economic analyst Transforma Insights forecasts.
IoT is constantly intertwined with the use of machine learning. For instance, machine learning, artificial intelligence, and deep learning are now used to make IoT devices and services smarter and better. In any such scenario, the benefits go both ways, provided that machine learning and AI need a tremendous amount of data to function effectively, precisely what the IoT sensor and system networks provide. For example, IoT networks may gather operational and performance information in the manufacturing plant in industrial settings, which is then analyzed by AI systems to improve the performance of the production system, promote productivity and predict when machines need maintenance.
Machine Learning In Hyperautomation
Hyperautomation, an IT mega-trend defined by Gartner, is the likelihood that almost everything inside a company that can be automated should be automated, such as legacy business processes. The pandemic has improved the acceptance of the term, otherwise referred to as digital automation of processes and intelligent automation of processes.
Machine learning and artificial intelligence are the main industries and major drivers of hyper-automation (alongside different innovations like process automation tools). Hyperautomation operations can’t rely on static packaged applications to be successful. Automated business processes need to be able to adjust to changing situations and respond to unexpected conditions.
Reinforcement Learning
Reinforcement learning (RL) is a field of machine learning that discusses how software agents can take action to maximize the reward in an environment.
