Machine Learning in essence is a way of teaching computers to provide more accurate predictions on provided data. These predictions can also make apps and devices smarter by providing recommendations as an outcome to the data.
In the pursuit of making roads safer, Toyota Canada has been capturing data from mechanics in all of Toyota Canada’s 300 dealerships on the vehicles they repair. In the past, the repair data was extracted from Toyota Canada’s service application manually and stored in databases on premise to later be analysed. While parts of the analytics process were automated, the entire process took over 6 months to process the reams of data to provide a part replacement recommendation. Toyota Canada wanted to reduce the process time and so approached Microsoft to collaborate in a Machine Learning Hackfest to come up with a solution.
While we are unable to detail the exact process undertaken by Toyota Canada and Microsoft as completed during the Hackfest itself, this post will walk through steps accomplishing a similar exercise to enable further understanding of the Machine Learning process. The step-by-step detailed below will set up a pricing prediction of specific vehicles.
Lets get started.
To see the full guide, please go to CANITPRO.
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