Tomas Larsson


Thought Leadership: Machine Learning & Data Science Talent Development

Machine learning can be described as the use of algorithms relying on patterns and inference, instead of detailed instructions of how variable should be used in models.  Machine learning comes in different shapes and sizes, with many companies investing in these capabilities.  As companies invest, it is important that discipline is used to ensure the quality of data output. Just think about it – you’re relying on this information to inform marketing investments that sometimes amount to hundreds of millions of dollars.  It is imperative that you get it right.

At BLEND360, Machine learning is one of the tools we use when developing models and strategies to support our clients.  The models are driving our clients ROI upwards in significant ways.  The use of Machine Learning can result in more efficient targeting and shorter model development times for our clients. It can also perform automatic tuning and continuous improvement of models as more data becomes available, making it a closed loop process.   

Thought Leadership Activities

  • Machine Learning, what is it, and how is ML different from AI?

  • Pros and Cons of Machine Learning techniques

  • The characteristics of a problems where ML can outperform classical modeling techniques