To achieve full understanding of the use and application of ML algorithms, our participants will work on a real-life industry project, translating theoretical knowledge to practical process and overcoming realistic challenges.
Scope:~400 work hours total
Data:Real data provided by company
Guidance:Experienced mentors provided by Y-DATA
Support:Weekly meetings with company data-owner
WixRecommendation System for Wix Dashboard Users
The “Discovery Feed” is the first personalized widget in Wix Dashboard. Its main purpose is to help users to discover more tools that Wix has to offer in order to finish setting up their site or help the user manage their business (depending on user’s current business status). When a user enters the dashboard, he is exposed to four different items (out of 25) and on the right he has a carousel that can reveal more items. The first four items and the priority of the rest of the items is currently chosen based only on business rules. The goal of this project is to use user activity data to increase user engagement by increasing their use of additional Wix tools as measured by increasing the CTR of the discovery feed product. The method for this is to create a personalised recommendation system which will select which items to display to each user.
Full project cycle
The process of working on the project follows popular industry standards and methodologies and incorporates a growing set of tools the students possess to methodically understand and solve a real-world problem. Our students have a full-cycle data science project in their portfolio upon graduation, covering all industry-standard stages: Business Understanding, Data Understanding, Data Preparation, Modeling, Evaluation.
Example ProjectAutomatic detection of low-value queries in technical Q&A forum
A customer operates a forum where programmers ask each other questions, provide answers and rate questions giving them \"ups\" and \"downs\". The forum has a core expert community that provides good answers and valuable insights. However, they often waste their time handling questions of little to no value: marking questions as duplicates and redirecting them, closing topics with incoherent or irrelevant questions etc. Because of this, the overall efficiency of the system suffers.