Following on from my blog post outlining an A-Z of Digital, here is “M for Machine Learning”.
Machine Learning (ML) allows a computer to learn and act without being explicitly programmed with that knowledge. For example, if you get a computer to recognise a picture of a car and show it some examples of a car, it will then be able to recognise cars going forward and apply what it has learnt against new pictures shown.
Machine learning tasks are typically classified into three broad categories, depending on the nature of the learning signal or feedback available to a learning system. These are
Supervised learning: The computer is presented with example inputs and their desired outputs, given by a “teacher”, and the goal is to learn a general rule that maps inputs to outputs.
Unsupervised learning: No labels are given to the learning algorithm, leaving it on its own to find structure in its input. Unsupervised learning can be a goal in itself (discovering hidden patterns in data) or a means towards an end (feature learning).
Reinforcement learning: A computer program interacts with a dynamic environment in which it must perform a certain goal (such as driving a vehicle or playing a game against an opponent). The program is provided feedback in terms of rewards and punishments as it navigates its problem space.
Machine Learning has opened a lot of uses and applications within business and industry such as a manufacturing process that looks for defects in products by telling the computer what good looks like, with imperfections being identified for further investigation.
One common place for interacting with Machine Learning is through the use of Chat Bots. You may have used a chat bot without knowing it, with machine learning helping to provide the answers to your queries.
An interesting chat bot to try out through Facebook Messenger is Keiko, a people search droid. The search can provide a series of questions to help narrow the search to who you are looking for. Yes you could do this through a normal search engine, but the thing I like about Keiko is the ability to interact and respond to the query with additional questions or suggestions for the search. Keiko can provide other functions other than just searching for a person. Search engines themselves have a lot of machine learning involved in ensuring that the results returned are the best match to the person searching and the search criteria.
If you want to have a go with a Machine Learning program try Googles Autodraw https://www.autodraw.com/. In this application you can draw an object and Google will try and suggest clip art that is similar to your drawing. As the program is used it learns from the drawings and selections that people make.
- Visual introduction to Machine Learning
- Deal or no deal? Training AI bots to negotiate
- How to get started with machine learning in manufacturing
- Putting machine learning into context
- How machine learning and AI are transforming the workplace
- Enrolling in Artificial Intelligence Kindergarten
- The digital twin
- Hesitant to adopt machine learning in 2017? This might change your mind
- Machine intelligence still requires gray matter
- Why artificial intelligence will never be smart enough to replace a good leader
- Is the fusion of AI and cloud the future?
- A primer on personal AI assistants
- Visual Introduction to Machine Learning
- In-depth Introduction to Machine Learning
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