Machine learning is a field of computer science that uses statistical techniques to give computer systems the ability to “learn” with data, without being explicitly programmed. Machine learning is closely related to (and often overlaps with) computational statistics, which also focuses on prediction-making through the use of computers. It has strong ties to mathematical optimization, which delivers methods, theory and application domains to the field. Machine learning is sometimes conflated with data mining, where the latter subfield focuses more on exploratory data analysis and is known as unsupervised learning.
There are many different types of machine learning algorithms, with hundreds published each day, and they’re typically grouped by either learning style (i.e. supervised learning, unsupervised learning, semi-supervised learning) or by similarity in form or function (i.e. classification, regression, decision tree, clustering, deep learning, etc.). Regardless of learning style or function, all combinations of machine learning algorithms consist of the following:
- Representation (a set of classifiers or the language that a computer understands)
- Evaluation (aka objective/scoring function)
- Optimization (search method; often the highest-scoring classifier, for example; there are both off-the-shelf and custom optimization methods used)
The fundamental goal of machine learning algorithms is to generalize beyond the training samples i.e. successfully interpret data that it has never ‘seen’ before.
If you are looking for the best Machine Learning jobs, you have come to the right place!
To recruit talent for Machine Learning in Sydney and elsewhere, contact us at Big Wave Digital today.
[button class=”btn white” url=”https://bigwavedigital.com.au/connect”]Connect with Big Wave Digital[/button]
“The secret of getting ahead is getting started.” , Mark Twain
[templatera id=”4407″]
