Stop asking your neural network to "Select one of the following ..." and start asking it to "Write a paragraph explaining ...". When you give your model more information in the training output, you are teaching your model from an essay instead of multiple choice. This increase of information can lead to an increase in accuracy and is why you should consider giving your model multiple "tasks" or problems to solve with prediction.

In this presentation, I will discuss how Hudl is using multi-task models to clip sports videos into plays and also how we determine the formation of an offense in American football. After we talk about what multi-task models are and how they can be used, I will share the some of the challenges we have run into that differ from a traditional model output.

Do you want to get started with data science without fighting crypto fanatics for GPU cards? Do you want to see what Azure has to offer for training/deploying models?

In this talk, I will walk through the whole process. I will start with setting up the job, I will show how to connect to your workspace, I will then submit the job for training, I will walk through validating the model, and finally I will deploy the model