Software labs is a company which prides itself in being industry leaders in the machine learning and data science field, but what is data science really and why does it go hand in hand with machine learning. Data science generally is a way of analysing data and creating mathematical models which can predict, classify or recommend outcomes based on data provided. Machine learning essentially is added to the mix in order to allow the machine to process these models and to provide highly optimised outcomes.
Types of machine learning
In the most sense machine learning can be divided into two different categories. Supervised and unsupervised learning. Supervised learning usually is applied to predicting outcomes, using a data set either in a scalar or vector space. This usually is achieved by providing a machine learning algorithm with a certain set of data where we know what the outcome should be then the algorithm will converge on certain weights or coefficients to create either linear, polynomial or some other type of model to predict outcomes of new data. Generally the accuracy of outcomes are measured by the R-Squared value which determines how good of a fit the model is to it’s data. Unsupervised learning mostly attempts to categorise or sort data into various classifications. Sometimes this could be a method of finding relationships between data where one was not even aware of the relationship, this often is used to discover useful relationships which otherwise could go unnoticed. Using this in accordance with other machine learning techniques can create deep insights into data.
What can machine learning be applied to?
Machine learning can be applied to a broad spectrum of fields.
- Machine learning can assist in research of medical cures.
- Uncovering hidden information in genetics.
- Predict user behaviour on a website.
- Image classification.
- Find out a great deal about your customers and their behaviour.
- Recommend products on a website based on buying behaviour.
And the list goes on and on …
If you wish to find out more about this please feel free to contact us or follow some of our tutorials on the subject to learn more.