Four steps to accelerate the journey to machine learning - SiliconANGLE

A good example of solving for the right problems can be seen in Formula One World Championship Ltd. The motorsport company was looking for new ways to deliver race metrics that could change the way fans and teams experience racing, but had more than 65 years of historical race data to sift through. After aligning their technical and domain experts to determine what type of untapped data had the most potential to deliver value for its teams and fans, Formula 1 data scientists then used Amazon SageMaker to train deep learning models on this historical data to extract critical performance statistics, make race predictions and relay engaging insights to their fans into the split-second decisions and strategies adopted by teams and drivers.