Intel’s sales and marketing organization strives to increase communications with resellers relating to new industry segments as they evolve and to encourage resellers to join webinars or conferences to gain a better understanding of Intel’s offerings for these new markets. Because sales and marketing teams must focus their resources on those resellers with the highest probability of generating sales, sending the right message to the right reseller helps drive value for the sales pipeline. We needed a machine-learning system to help our sales and marketing teams identify the best prospects within Intel’s large pool of resellers.

In this case study, the challenge explored involves LeNet*, one of the prominent image recognition topologies for handwritten digit recognition.   In the case study, we dive into how the training tool can be used to visually set up, tune, and train the Mixed National Institute of Standards and Technology (MNIST) dataset on Caffe* optimized for Intel® architecture. Data scientists are the intended audience.