Dr. Raoul-Gabriel Urma, CEO
2017 Photo Highlights
Packed full of inspiring keynotes and practical workshops and numerous networking opportunities.
Representing a range of sectors, from research and bioinformatics to business and finance.
Covering Exploratory Data Analysis and Machine Learning using Python.
Prof. Sunil Vadera
Professor, University of Salford
Session: Research Challenges in Applying Data Mining
Abstract: This talk outlines the future challenges that need to be addressed if Big Data Analytics is going to be successful in addressing regional and global challenges including managing energy consumption, climate change, finance, health and social inclusion.
Session: Introduction to Deep Learning and Natural Language Processing
Abstract: Using Machine Learning and vector representations of text for Natural Language Processing has been around for a long time but with recent developments in neural networks and dense representations it has become the de facto standard for many NLP tasks.
Partner, Appleyard Lees
Session: An overview of patent activity in machine learning
Abstract: We live in a world where a vast quantity of digital data is generated on a daily basis – an often-quoted statistic is that 90% of the world’s data was created in the last two years. The prevalence of these “big data” sets has opened the flood gates for the application of machine learning to solve an enormous variety of problems, from bioinformatics to FinTech. This surge in the application and sophistication of machine learning has been accompanied by a corresponding surge in patent filings over the last few years. As innovators developing better algorithms, or apply them to new problems, they seek to protect their inventions. Julia Gwilt will lead you on a tour through the machine learning patent landscape.
Head of Analytics, Hello Soda
Session: Deploying Machine Learning Models as A Service
Abstract: In this session, Leanne will take us through how Hello Soda have developed the in-house ability for data scientists to deploy their data products and models directly into a live production environment. Leveraging a modern technology and open source stack - including the use of Docker and a cloud based micro-services infrastructure - Hello Soda have enabled code agnostic model deployment such that the data scientist can be an active participant in the complete model and data product lifecycle, regardless of their preferred coding language. Leanne will explore why there was a need for such a solution, why third party solutions were not meeting the needs, and how the in-house solution has been incorporated in addition to discussing the next series of challenges faced.
Dr. Erol-Valeriu Chioasca
Session: AI Systems for Requirements Quality and Compliance
Head of Data Science R&D, Peak
Session: Data Science for Business
Session 1: Data Science essentials
- Supervised vs. Unsupervised Learning
- The Numpy library for array manipulations
Session 2: Data Analysis using Python
- The Pandas library for data manipulation
- Data cleaning and pre-processing
- Data visualisation with Matplotlib
Session 3: Machine Learning Techniques
- The scikit-learn library for Machine Learning
- Applying Principal Component Analysis
- Conference talks are suitable for all individuals looking to get insight into the latest data science topics, applications and key challenges faced in industry.
- Workshops will assume some basic knowledge about programming in Python. You can acquire these skills at our Python bootcamp.
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