Jim Harris says people still play a pivotal role in data-driven decision making.
Jim Harris says people still play a pivotal role in data-driven decision making.
Applying machine learning approaches to forecasting is an area of great research interest. Progress is being made on multiple fronts, for example: In the M4 Forecasting Competition, completed earlier this year, the top two performers utilized machine learning with traditional time series forecasting methods. At the link you'll find full
There are four widely recognized styles of machine learning: supervised, unsupervised, semi-supervised and reinforcement learning. These styles have been discussed in great depth in the literature and are included in most introductory lectures on machine learning algorithms. As a recap, the table below summarizes these styles. For a comprehensive mapping