Background

The emergence of Data Science is considered to be a great advance in the domain of modelling. The abundance and the explosive growth of recorded data in recent years has added a new dimension to the established paradigms of theoretical, empirical and computational modelling; these are now augmented by data driven modelling. Data Science encompasses the established domains of data warehousing, data mining, cluster analysis, pattern classification, machine learning and data visualisation. The application of Machine Learning in general and Deep Learning in particular, to very large data sets, has led to ground-breaking progress in recognising patterns of sounds, images, & data.

The human brain finds it difficult to make sense out of very large volumes (peta bytes) of unstructured data. Yet Deep Learning can discover hidden ‘connections and patterns’. Humans are not able to model these ‘connections and patterns’ because their cognition power limits them in making sense of these very large data sets and their inherent complexities.

This event brings together experts from industry and academe to explore and discuss the major advances and applications of these technologies.
Come along and open up to the new era of AI, Machine Learning and Deep Learning and find out how this can help you and your organisation in an increasingly ‘data-driven world’.

In addition to the conference, there are three pre-conference workshops:

1. Practical Deep Learning with TensorFlow

2. AI in Multimedia

  Presentation 1: Leveraging Deep Learning for Image and Text
  Presentation 2: Redefining Text Analytics: using deep learning for image and audio analysis

3. Deep Learning Fundamentals

Who should attend

  • Academic Researchers
  • Big Data Analytics Experts
  • Business Analysts
  • Chief Digital Officers
  • Chief Information Officers
  • Chief Marketing Officers
  • Chief Technical Officers
  • Data Architects
  • Data Engineers
  • Data Scientists
  • Developers
  • Development Managers
  • Director of Engineering
  • Enterprise Architects
  • Entrepreneurs
  • Heads of Data and Analytics
  • Machine Learning Scientists
  • Venture Capitalists
  • VPs and Executives within Marketing | Development | Engineering | Technology | Sales

Call for Participation

We are looking for Use Case Presentations on AI, Machine Learning and Deep Learning, particularly in the industry sectors of

  1. Retail
  2. Pharmaceuticals
  3. Health
  4. IOT
  5. Communications
  6. Energy

and others. If you wish to submit a proposal to present at this event please fill in the speaker’s response form.

Programme

  • 08:30 -

    Coffee and Registration

  • 09:30 -

    Start of conference – Chairperson’s introduction and welcome

  • First Session Chairperson: Professor Gautam Mitra, OptiRisk Systems/UCL -

  • 09:35 -

    Keynote: Foundations of Deep Learning, illustrated with use cases

    Bianca Furtuna, Data Scientist at Elastacloud

    What is the future going to look like? When are we going to reach true Artificial Intelligence? Is the Singularity going to happen? There is a lot of talk today about AI and what it means for human society. Let's forget about the future for now and focus on what is possible today. We are going to look at the most promising area in AI research, Deep Learning and understand how it fits in the wider picture of Machine Learning. We are going to explore the fundamentals of Deep learning and deep dive into some common use cases to illustrate the applications of the technology in the real world.

    Speakers:

    Bianca Furtuna

  • 10:05 -

    Artificial Intelligence and Machine Vision: The next frontier for process efficiency and integrity

    Bogdan Ciubotaru, CTO, Everseen Ltd

    ♦ Process efficiency and integrity represent two main factors impacting many sectors including retail, manufacturing and transportation
    ♦ Vision has always been a critical information source, however it is mainly specific to human observers and hence difficult to use effectively
    ♦ Machine vision and artificial intelligence open the door for a wide range of applications including efficient process management
    ♦ The positive impact on various businesses and industries has already been proven with great growth envisioned for the future

    Speakers:

    Bogdan Ciubotaru

  • 10:35 -

    Coffee break

  • Second Session Chairperson: Jochen Leidner, Director, Research, Thomson Reuters -

  • 11:00 -

    Becoming Cognitive: How to Transform Your Business

    Josh Sutton, Global Head, Data & AI, SapientRazorfish

    AI is going to disrupt nearly every industry at a faster pace than we have ever seen. Tomorrow’s success stories will be those firms that became a cognitive business. This presentation will discuss pragmatic, real world approaches for identifying meaningful uses for AI within your organisation today. It will outline the seven steps for cognitive transformation within an enterprise business. The audience will gain a high level understanding of how to build a cognitive platform for their organisation inclusive of technology, experience, and change management that avoids creating silos and demonstrates meaningful business value in months instead of years.

    Speakers:

    Josh Sutton

  • 11:25 -

    AI in Production: How super-intelligence becomes dumb

    Alistair Ferag, Senior Data Scientist, Satalia

    Satalia creates production-grade data science and optimisation solutions for a range of clients and ever aspire to develop AI into them - but this can be tough. Leaving AI solutions in production with no oversight can lead to unintended consequences. This talk will discuss approaches to apply AI and provide a demo to highlight how difficult it can be to operationalize.

    Speakers:

    Alistair Ferag

  • 11:50 -

    The most critical selection criterion

    Gert De Geyter, Senior Consultant Data Analytics at Deloitte Belgium

    As data scientists, we often spend a long time optimizing and endlessly trying to refine our models. All too often, this ends up in neglecting what may be the most important selection criterion: acceptance by the end user. In this talk, some tips and tricks are shown using real case examples how to improve to odds of convincing critical end users.

    Speakers:

    Gert De Geyter

  • 12:15 -

    Comparing Notebooks for Data Science

    Karlijn Willems, Data Science Journalist at Datacamp

    Data science requires more than traditional Integrated Development Environments (IDEs) can offer: the need to create and share data stories. That's why data scientists often resort to notebooks. In her talk, Karlijn Willems will guide you through the landscape of data science notebooks, from Jupyter to Beaker to R Markdown to Zeppelin and more, providing a comparison between the different notebooks that are out there for data science enthusiasts!

    Speakers:

    Karlijn Willems

  • 12:45 -

    Speaker Panel and Q&A Session

  • 13:00 -

    Lunch

  • Third Session Chairperson: Jochen Leidner, Director, Research, Thomson Reuters -

  • 14:00 -

    Intelligent Information: R&D and Innovation in Information Access at Thomson Reuters

    Jochen Leidner, Director, Research, Thomson Reuters

    The Information economy combined with progress in computer performance and progress in machine learning pose great opportunities.  In this talk, I will give some case studies of research projects conducted at Thomson Reuters Corporate Research & Development group, where we strive to improve information access for professional knowledge workers in different vertical domains, often applying machine learning to applications in information and information retrieval.

    Speakers:

    Jochen Leidner

  • 14:30 -

    Using Data Science for Underwriting and Risk Analytics for Unsecured Instalment Loans

    Aditya Satyadev, Co-founder & CEO, BizAcuity Solutions Pvt. Ltd.

    ♦ Unsecured Instalment Loan Business and Complexity
    ♦ Conventional rule based Underwriting Vs. Data Science Based Underwriting
    ♦ Paradigm shift in Risk Management due to accessibility of in-house and global data
    ♦ Solution Architecture – Data Integration/Wrangling, Data Quality, Technology Stack
    ♦ Building the Model with Data Science and Deep Learning Algorithms
    ♦ Model Assessment and Optimization
    ♦ Business Impact Analysis
    ♦ Operationalization of Solution with Human Touch

    Speakers:

    Aditya Satyadev

  • 14:55 -

    Deep Learning is back and how enterprises can leverage it!

    Tarry Singh, Data Analytics Executive, Entrepreneur

    "Tarry will give a whirlwind tour of the world of deep learning. How it all started -- yes, your linear algebra and spherical trigonometry is back. Explore the inner workings of how Deep Learning actually works -- how ANNs work and how they still have a long way to go before really understanding how human brain works. Then he will take a practical dive into how companies actually try to put this is practice and create great products and services. And if time permitting he will give a quick tech walkthrough into one of his AI projects from his upcoming book titled 'Practical AI / Deep Learning Projects' "

    Speakers:

    Tarry Singh

  • 15:05 -

    Speaker Panel and Q&A Session

  • 15:20 -

    Tea Break

  • Final Session Chairperson: Professor Gautam Mitra, OptiRisk Systems/UCL -

  • 15:45 -

    Networks are like onions: Practical Deep Learning with TensorFlow

    Barbara Fusinska, Data Scientist

    Deep learning is the area that wins over the field of Artificial Intelligence. By using libraries like TensorFlow, it is now available to the wider audience. In this tutorial, Barbara will walk the audience through the process of creating several types of neural networks. The session will start with explaining key concepts of deep learning and introducing datasets the computation will be performed on. Along the way, attendees will have the practical opportunity to use TensorFlow to build deep networks, train them and evaluate the results. After the session, participants will become familiar with how to use TensorFlow when shaping the architecture of neural networks. By the hands-on form of the tutorial, the audience will have the chance to gain some firsthand experience of how to apply deep learning to computer vision and natural language processing tasks.

    Speakers:

    Barbara Fusinska

  • 16:15 -

    Applications of Deep Learning in Business

    Armando Vieira, Data Scientist, ContextVision AB

    Despite being a relatively new research field, Artificial Intelligence (AI) history has been shaped by huge expectations and colossal failures. After several stagnation periods or "long winters", AI is flourishing as impacting business at an unforeseen pace. Behind this success is a technology widely known as Deep Neural Networks or Deep Learning (DL). In this talk Armando summarizes the key elements of DL and why it is such a transformative force for almost every business.

    Speakers:

    Armando Vieira

  • 16:45 -

    Chairperson’s summary

  • 17:00 -

    Close

Speakers

Bogdan Ciubotaru

CTO, Everseen Ltd

Alistair Ferag

Senior Data Scientist, Satalia

Bianca Furtuna

Elastacloud

Barbara Fusinska

Data Scientist

Gert De Geyter

Senior Consultant Data Analytics at Deloitte Belgium

Jochen Leidner

Director, Research, Thomson Reuters

Aditya Satyadev

Co-founder & CEO, BizAcuity Solutions Pvt. Ltd

Tarry Singh

Data Analytics Executive, entrepreneur

Josh Sutton

Global Head, Data & AI, SapientRazorfish

Armando Vieira

Data Scientist, ContextVision AB

Karlijn Willems

Data Science Journalist at Datacamp

Sponsors

Media Partners

 

 

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Venue

  • NOVOTEL LONDON WEST
    1, Shortlands, W6 8DR, LONDON, UK
  • +44 (0) 208 237 7755
  • info@unicom.co.uk

Contact Us

  • UNICOM R&D House | One Oxford Road | Uxbridge | UB9 4DA
  • +44 (0) 1895 256 484
  • info@unicom.co.uk
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