over 1 year ago
Machine Learning is one of those data science terms that gets conflated with many other things related to the field (such as Artificial Intelligence, advanced statistics, deep learning, etc.). This is probably because many people use it loosely to describe a skill-set they require for a data science position, without wanting to get too specific so that they don’t deter certain people they may still be interested in. Also, many bloggers talk about machine learning because they are aware that it is a popular phrase worth a lot in terms of SEO, so they tend to include a lot of things under the machine learning umbrella.
In our experience, machine learning is a large set of techniques, widely used in industry-related data science as well as in research centers and universities (where most of these techniques came from in the first place). These techniques include mainly non-statistical methods for classification or regression, such as decision trees, random forests, support vector machines (SVMs), artificial neural networks (ANNs), k nearest neighbor, etc., techniques that are often referred to as supervised learning. Machine learning also includes unsupervised learning methods, such as association rules, k-means, and DBSCAN (the latter two are popular clustering methods). Machine learning is not the same as artificial intelligence, although there is a big overlap between the two groups (e.g. ANNs). Beyond these fairly popular machine learning methods, there are also several others that tend to be more relevant for specific applications (e.g. recommender systems). As a result, when recruiting a machine learning expert, it is best to have a clear idea of the problem at hand, since you may need a specialist in a particular machine learning technique, rather than a machine learning generalist, or vice versa.
For more information on machine learning recruiting, and for a run-down of whom we currently have available for contract and permanent positions, please contact ResourceFlow’s Machine Learning Recruitment specialist – Chris Wright on + 44 208 133 0822 or firstname.lastname@example.org
Tags: supervised learning, unsupervised learning, Data science, artificial intelligence, machine learning, Data science terms, Data science position, deep learning, Field, Statistics, People