DSF Day 1 - Data Science at Scale hosted by King

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DSF Day 1 – Data Science at Scale hosted by King

Join us for an evening of tech talks focused on Data Science at scale. Featuring two King speakers discussing real-world data science problems from the game analytics space.

The evening will also include Rafah El-Khatib who joins us from the advanced analytics on machine learning applications department at ING. Rafah will discuss selecting predictive features to input into a model when you are dealing with data at scale.

Please click here to apply for a ticket: https://2019.london.datasciencefestival.com/event/dsf-day-1-king/


6.00pm - Doors open

6.30pm- 2 x 20 minute talks from King

7.15pm - Drinks food & networking

7.45pm – Rafah El-Khatib

8.30pm - Networking

9.00pm - Close

Address: 178 Wardour St, Soho, London W1F 8FY

Rafah El-Khatib - Data Scientist at ING

Summary: Feature Selection Best Practices - LOFO and a Survey of Key Feature Importance Packages.

Selecting predictive features to input into a model is key to ensuring that the input data is not noisy and is time-effective in cases where the original number of features or dataset are large. In this talk I will present a survey of key feature importance packages and explain their strengths and weaknesses, and I will present an in-house open-source feature importance package called LOFO (leave-one-feature-out) and its fast approximation (FLOFO, or Fast LOFO). The LOFO importance calculates the importances of a set of features based on a metric of choice, for a model of choice, by iteratively removing each feature from the set, and evaluating the performance of the model, cross-validated, based on the chosen metric.

Bio: Rafah El-Khatib is a data scientist at ING Bank, working within the Financial Markets and Advanced Analytics departments on machine learning applications in financial investments and trading. She received her B. Eng in Electrical and Computer Engineering from the AUB, Lebanon, where she did research on software verification and signal processing, and her Ph.D. in Computer and Communication Sciences from EPFL, Switzerland. Her research interests include the design and analysis of coding systems with a focus on graphical models, as well as signal processing more generally, and machine learning.

Due to the popularity of Data Science Festival events, we are now allocating event tickets via a random ballot. Registering here enters you into the ticket ballot for the Data Science Festival Event at King on April 8th 2019, the ballot will be drawn on the 1st April 2019. Those randomly selected will then be e-mailed tickets for the event, with the joining details.
If you get an allocated ticket, please bring a copy of your paper ticket or your ticket on your phone to the event to check in with your QR code. Tickets are non-transferable.

The Data Science Festival is the first of its kind as the only community led, free to attend Data Science Festival in the UK.