COGNITIVE FINANCE GROUP - public speaking engagements and Boards presence in Q1 2017
A.I. & customer engagement “What to do with it and win”, invitation-only dinner, London, Jan 2017
Pension Administration Forum, London, January 2017, an Incisive Media event
Robo-Investing Conference, panel with Paolo Sironi, Francesco Brenna (IBM), Richard Peers (Microsoft), Blake Wood (Envestnet), Alois Pirker (Aite Group), London, February 2017
Digital Transformation in Wealth & Asset management Summit, London, February 2017
ITAS asset management annual conference, Neumunster, Luxembourg, February 2017
A.I. in wealth management, invitation only roundtable, London, February 2017
Use cases in insurance, invitation only private dinner, London, March 2017
REGULATORY, PUBLIC POLICY AND A.I. GOVERNANCE
NAS/Royal Society panel with Vint Cerf, Greg Corrado, Peter Stone, Austin, TX, January 2017
Expert Advisory Board of the All Party Parliamentary Group on AI at UK Parliament. March 2017
IEEE Global Initiative for Ethical Considerations in Artificial Intelligence, Austin, TX, March 2017
Artificial Intelligence” documentary Canadian Broadcasting Co. Radio March 2017
Interview on AI with French National TV station France 24 March 2017
Webinars on Brighttalk.com
Panel Discussion: AI & Machine Learning in Cyber Security
A live online panel discussion focused on the debate around AI and machine learning and how they can automate cyber security; catch more threats and malicious attacks and prove a useful weapon against cyber crime.
Data Science Apps: Beyond Notebooks with Apache Toree, Spark and Jupyter Gateway
Jupyter notebooks are transforming the way we look at computing, coding and problem solving. But is this the only “data scientist experience” that this technology can provide? This webinar, sketches how you could use Jupyter to create interactive and compelling data science web applications and provide new ways of data exploration and analysis.
AI in Finance: AI in regulatory compliance, risk management, and auditing. How AI identifies and prevents risks, above and beyond traditional methods. Techniques and analytics that protect customers and firms from cyber-attacks and fraud. Using AI to quickly and efficiently provide evidence for auditing requests. Learn how to use Machine learning and cognitive computing for:
GLOBAL ARTIFICIAL INTELLIGENCE CONFERENCE, Santa Clara, CA, USA, January 2017
AI for Financial Applications
We all love AI. But what about financial applications? It turns out that AI, and in particular ML and DL can be very effectively applied to financial services. This presentation illustrated a number of use cases such as transaction fraud prevention and credit authorisation using AI and machine learning techniques. Starting from there, the presentation will show how those problems can be solved with AI techniques with code snippets and live demos using Keras, Tensorflow and Scikit-Learn applied to some financial datasets. It will then describe how techniques such as deep learning, t-sne, dimensionality reduction can be used as the "data engines" for the next-gen financial applications both in retail as well as commercial banking.
PREDICTIVE BUSINESS ANALYTICS & DATA MANAGEMENT FORUM Milan, Italy February 2017
Are we reaching a Data Science Singularity? How Cognitive Computing is emerging from Machine Learning Algorithms, Big Data Tools, and Cloud Services.
Prescriptive analytics is the ultimate analytical step which goes beyond predictions into the realm of goal-oriented recommendations. As such, we could consider prescriptive analytics as a particular sort of cognitive computing. In 2016, how far are we from cognitive computing actually? Will Cognitive Computing emerge from Machine Learning Algorithms, Big Data Tools, and Cloud Services?
DATA DRIVEN INNOVATION, Open Summit, Rome, Italy, March 2017
Data Science Apps: Beyond Notebooks. Jupyter notebooks are transforming the way we look at computing, coding and problem solving. But is this the only “data scientist experience” that this technology can provide? This talk will sketch how you could use Jupyter to create interactive and compelling data science web applications and provide new ways of data exploration and analysis. In the background, these apps are still powered by well understood and documented Jupyter notebooks.
SAFARI Book online
Geolocated clustering and prediction services with scikit-learn (Oriole Online Tutorial)
Geo-Located Data: Extracting Patterns from Mobile Data Using Scikit-Learn and Cassandra (an introduction to extracting patterns from geo-located data and building geo-located micro-services)
jupyterhub-ansible-deploy: provisioning a datalab with jupyterhub and data science libraries for Python, R, & Scala
ansible-role-centos-jupyterhub: Jupyterhub on CentOS 7, configurable spawner (sudo, docker), jupyter lab support