1 DAY CONFERENCE

Data Science Festival 2017

Topics covered at #datasciencefest

Saturday, 29th April in London

22 experts spoke.

Overview

The Data Science Festival was a free, week long, annual, celebration of all things data science. The festival consisted of lectures, workshops, demos, code sprints, panel discussions and social events, spread across London.

The aim was to connect the data science community and foster the sharing of knowledge, inspiration and ideas. CodeNode was the venue for the Data Science Festival on Saturday, 29 April 2017.

Who is the Data Science Festival for?

  • Data engineers, analysts, scientists, and other practitioners

  • R, Python and other software engineers who work with data or want to learn

  • Data visualisation developers and designers

  • Non-technical team leads, executives, and other decision makers from data centric startups and large companies looking to utilise open source tools

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Programme

Day 1: Saturday 29th April

Check out these awesome sessions below!

Track CTRL ALT/TAB CMD
09:00

War in HD: Conflict and Open Source Infomation

Nick Waters


open course conflict analysis mobile data-science-fest

How can we predict a successful data science project?

Jay Lui


data-science data-science-fest
09:45

A Beginners Guide to Weather and Climate Data

Margriet Groenendijk


climate bigdata machine-learning models data-science-fest

Less is More: Data Visualisations for Big Data

James Cheshire


complex-datasets data-visualisation big-data data-science-fest
10:30

Coffee Break

11:00

Learning at hyper-scale: creating the self-learning business

Mike Hyde


big data self-learning bigdata architecture data-science-fest

Using AI to understand Human Behaviour in the workplace

Ankur Modi


ai human-behaviour operational-visability data-science-fest

A practical look at putting data science in production

Shahzia Holtom


smart-search support-vector-machine agile-practices app data-science-fest
11:45

Word Embeddings for Natural Language Processing in Python

Marco Bonzanini


natural-language-processing python data-science-fest

One-by-one Is No Fun: Lessons learned writing Kafka ETL jobs

Dean Morin


kafka one-by-one-processing data-science-fest

Behind the scenes of training, managing and deploying machine learning models

Pawel Subko


commercial-machine deep-learning data-science git docker neptune data-science-fest
12:30

Lunch

13:15

What “50 Years of Data Science” leaves out

Sean Owen


big-data critique statistics computer-engineering apache-hadoop spark data-science-fest

Anomaly Detection: A breakdown of Twitter’s Seasonal Hybrid ESD

Peter Tillotson


data-learning seasonal-hybrid-esd twitter data-science-fest

The Science of Visual Interactions

Miriam Redi


machine-learning web-media-search advertising social-media data-science-fest
14:15

Handling 1st line technical support with a chatbot

Barbara Fusinska


ai machine-learning chatbots natural-language-processing data-science-fest

Interactively Analyse 100GB of Data using Spark, Amazon EMR and Zeppelin.

Raoul-Gabriel Urma


big data python data-processing data-science-fest
2

Fashion Recommendations at ASOS: Challenges, Approaches and Learnings

Soraya Hausl and Roberto Pagliari


recommender-systems fashion-domain visual-browsing data-science data-science-fest
15:00

COFFEE BREAK

15:30

I went to work as an SQL programmer, and left as a hostage.

Peter Moore


case-study sql programming data-science-fest

How to Improve your Recommender System with Deep Learning: A Use Case

Alexandre Hubert


deep-learning recommender-systems dataiku data-science-fest

Reinventing Shop Direct’s customer contact strategy

Simon Hill


online-retailer communication-strategy data-learning data-science-fest
16:15

From PhD to life: using science to get a job in data

Gianluca Campanella


machine-learning quadratic-programmes linear-regression robust-regression python financial-planning data-science-fest

One of the most notable additions to the Microsoft BI stack is the addition of Microsoft R Server inside SQL Server 2016.

Oliver Frost


microsoft-bi sql-server data-science machine-learning scaler data-science-fest
Sponsors

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