Our news and views relating to Data Analytics, Big Data, Machine Learning, and the world of Credit.
Machine learning and artificial intelligence are exciting fields, and we've been writing about these topics for a couple of years now. While a lot of what we talk about on our blog is advanced implementations of machine learning and can be overwhelming to beginners, the core concepts of machine learning are actually pretty easy to grasp. There are many resources and cheat sheets available online, but we believe the old fashioned way of learning is sometimes the best: with a good book. Few resources can match the in-depth, comprehensive detail of a good book.
Our data scientists are keen readers and avid podcast listeners. In this blog, we list a few of the podcasts that cover topics such as data science, machine learning and artificial intelligence, and that we’d recommend if you’re looking to start exploring the world of podcasts.
In this blog, we’ve created a (non-exhaustive) list of courses you should consider if you want to learn essential data science skills in South Africa. These courses are mostly classroom training from South African institutions, but if you’re more interested in online learning, check out our blog Where To Learn Essential Data Science Skills Online.
We are quite proud of the ability to develop performant, stable and trustworthy predictive models here at Principa. For nearly 20 years, we have been developing predictive models that have helped so many of our clients to make better decisions, more often than not outperforming what our best competitors can achieve. The models that we have historically developed can be categorised as part of the additive group of models – that is, a handful of predictive characteristics are selected and classed in a way that best separates the ‘goods’ from the ‘bads' (i.e. the traditional binary classification application). Depending on the new unseen data, the resulting weightings are then added together to get a final score. For example, consider a 3-feature model that uses only Home Ownership, Years at Employer and Age. Let's say you are a homeowner and for this you get 10 points, you have been with your employer for 5+ years (15 points), and you are 23 years of age (8 points), then your final score is 33, and the strategy will use this score and decide where you should go in the business decision tree.
The value and benefits of becoming a data scientist or picking up basic data science skills, cannot be overstated in today’s world. Businesses across all industries are starting to embrace data analytics and those who aren’t will soon feel the advantage gained by their competitors who are.