An Introduction to Machine Learning

Machine Learning and Neural Networks/Deep Learning are complex but rewarding ways of using and processing data that will help technology and automation in the future to become smarter and more dynamic. There is a popular theory that it takes 10,000 hours of training for someone to be ‘good’ at something and even then, they are still more likely to make errors on occasion – hence the term human error. The success of Deep Learning comes from the speed and precision with which the network is trained, often taking much less than 10,000 hours. In fact, a Neural Network can be trained in as little as a couple of hours, to a couple of days to be more efficient, faster and able to process more data than a human, or specialist programs. Advances in detection, analysis and problem solving have already simplified many processes. These advances are not only making an impact on our everyday lives, but are being hailed as a game-changer for robotics & automation for its Vision, Picking, Movement and Data areas implications.

“A branch of the Artificial Intelligence, Machine Learning is opening up entirely new possibilities in the world of automation. Machine Learning is a class of algorithms that learn from data through supervised or unsupervised means”.

We can already see the uses of Machine Learning in everything from healthcare, to E-Commerce to autonomous vehicles. While automation and robotics have been simplifying and helping with the most dangerous of industrial tasks since inception, Machine Learning is the next step in refining and streamlining many automated processes, furthering many industries and improving existing systems.