Inspiration
What it does
Accelify is a web application that recommends ServiceNow Technical Accelerators to companies with a trained, self-adaptive PyTorch model.
How we built it
We generated a dataset using the provided company and product information as the input and calculated the output by relating products to each other and to the industries they were used in. We designed and built a PyTorch model that could handle a variable number of products for each company and updates parameters as the number of ServiceNow's products increases.
Challenges we ran into
A challenge we ran into with machine learning was how to handle an increase in the number of products as the model's output was shaped around the number of products so when there was an increase, we designed the model to modify its architecture while retaining the learned parameters.
Accomplishments that we're proud of
An accomplishment we're proud of is designing and implementing a dataset and PyTorch model for a recommendation system where the model has a variable length of input and output.
What we learned
We learned how to transfer model parameters between PyTorch model layers and use embedding and padding to handle variable input.
Log in or sign up for Devpost to join the conversation.