PyData Tel Aviv Meetup: Modeling Multi-Destination Trips with RNNs Sarai Mizrachi

PyData Tel Aviv Meetup #26
14 August 2019

Many real-world problems naturally give rise to sequential data. Language models are already widely used to tackle computational problems related to natural language. We would like to present a non-NLP example by walking through a solution to the problem of recommending next destinations to customers who are taking a single trip to multiple cities using RNN-based sequence modelling. The problem becomes more complex if we have token-level, and/or sequence level features that we want to factor in. For example, we may want to use a sequence-level feature such as booker's country, as well as token level features like past bookings' lengths of stay, travel season, accommodation type, etc.

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

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