Ever since the concept of Artificial Intelligence emerged, it became one of the most talked-about trends in the world. People see AI as “the new normal” as it has made its way into different work processes in all most all kinds of industries from augmented analytics to facial surveillance.
Throughout 2018, we saw an incredible surge in platforms, tools, and applications focused on AI-and Machine Learning technologies. Ai and ML started in the internet and software trade, but now, we can also see them in different aspects of manufacturing, agriculture, healthcare, and more.
Experts believe that 2019 will be a significant year both for AI and Machine Learning. These technologies provide several applications in the real world that show their hidden value and benefits to consumers.
While these technologies still have a long way to go before we can consider them as mainstream, it’s exciting to see these trends emerging. To give you a better idea of what’s currently happening, take a look at these top Machine Learning trends of 2019:
When it comes to machine learning, robotics is one of the most advanced developments we have seen. Some people also feel wary about the rapid advances in robotics. That’s probably because of all the popular culture that portrays about robots taking over the world and making millions of people jobless.
In reality, robotics isn’t as sinister as believed to be. Our ability to adapt to Machine Learning has caused us to rely heavily on robotic process automation. Nowadays, intelligent robots and drones dominate the world of the technological revolution. We now see the use of robotic process automation in health, manufacturing, and finance processes where tasks become much easier because of robots.
All companies need to create their data within error records, log files, and status reports. However, the processes used for creating this data don’t reach the same level as the standards of machine learning.
Sarah Taylor, IT expert from AssignmentMan, a service that provides assignment help has seen this problem arising in her setup. Due to the nature of business her company is in, they soon had to utilize ML for data processing.
She says that companies now choose to utilize machine learning to gather and refine data then come up with smarter business insights, thus, making IT businesses proactive instead of reactive.
Mike Hasson who’s also working with a dissertation service has been through a similar situation. He presented his thoughts in bestessays review. He concurs that the algorithms of machine learning support various IT operations to get to the root cause of issues and ensure enhanced services. It has also proved to be very dynamic and highly beneficial in the customer service area by enhancing the troubleshooting rate and providing better solutions to the customer queries.
Transfer learning is one of the most popular types of machine learning techniques. In transfer learning, a model gets developed and trained for a specific task. Then it’s reused to perform other similar tasks.
For instance, you may train a basic classifier to determine whether images contain palm trees. You can utilize the knowledge the classifier gained during its development for the recognition of other objects like other types of trees.
This particular machine learning technique became hugely popular as is allows for a faster approach to learning, even deep learning. For this technique, you can use models that have been pre-trained from open-sourced networks as your starting point for natural language and computer vision applications.
