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Target audience: Data Scientists, Big Data developers and product managers, who are interested in recommendation systems Abstract: In today’s digital world, where the number of choices a user face within one application can be overwhelming, and user engagement is a key success factor, recommendation systems help users find items of interest. This meetup will consist of two sessions. The first session, will provide a brief introduction to recommendation systems, basic algorithmic approaches and possible implementations. In the second session, participents will see a step by step implementation of a simple recommendation system in Spark. What will you learn: • Motivation • Problem definition • Main algorithmic approaches: o Collaborative Filtering o Content-based Methods o Hybrid Methods • Evaluation metrics • Implantation tools • Recommendation systems in Spark Presenters: Shahar Cohen, https://il.linkedin.com/in/shahar-cohen-a606017 Oren Razon, https://il.linkedin.com/in/oren-razon-4b920031
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