DSF Day 1 – Data Science at Scale hosted by King
178 Wardour St, Soho, London W1D 2HP, UK
51.5155344
-0.13537780000001476
Description
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.
Schedule:
6.00pm - Doors open
6.30pm- Rupali Singhal & Piergiorgio Calzi
7.15pm - Drinks food & networking
7.45pm – Rafah El-Khatib
8.30pm - Networking
9.00pm - Close
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 importance 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.
Piergiorgio Calzi - Data Scientist
Summary: Lesser known tips and tricks for Pandas. Any Python user performing data analysis has used Pandas at a certain point. A handful of functions can get you by and allow you to achieve surprisingly good results throughout the data preparation stage. However, and perhaps less often, we face more challenging data preparation tasks. This talk will highlight some of the less common pandas features. Not exactly a 101 but maybe a 102.
Bio: Piergiorgio Calzi studied Business Management at Universita’ delgi studi di Trieste in Italy and Business Information Systems Management at Middlesex University, London. He has spent the majority of his career working within the gaming industry (Square-Enix and King) with a specialisation in advertising measurement. Most recently, he has been focused on the creation and productization of first and third party ad impact measurement solution.
Rupali Singhal - Marketing Analyst
Summary: Data Rich Marketing at King
Bio: Rupali Singhal is a Statistics post grad who has been working in Marketing Analytics for almost 5 years. A lot of her work has been based on Econometrics, optimising media across Tech, Banking and Telecom industries. At King, she sits within the Marketing function, helping shape our marketing strategy.
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.
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Start:
2019-04-08T18:00:00+01:00
End:
2019-05-02T21:00:00+01:00
Category
Tech
Tickets