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In The Press Archive - Faculty


Faculty shall notify the User without undue delay, in the event that any Personal Data held by Faculty on the User or on behalf of the User is lost, stolen, or where there has been any unauthorised access to the Personal Data which is likely to result in a high risk to the User's rights or freedoms. Furthermore Faculty undertakes to cooperate with the User in investigating and remedying any such security breach. In any security breach involving Personal Data, Faculty shall immediately take remedial measures, including without limitation, reasonable measures to restore the security of the Personal Data and limit unauthorised or illegal dissemination of the Personal Data or any part thereof. Faculty maintains documentation regarding compliance with the requirements of the law, including but not limited to documentation of any known breaches and holds reasonable insurance policies in connection with data security.

Student and Faculty Guide – 10 easy steps to get up and running with Azure Machine Learning


My colleague Amy Nicholson is the UK expert on Azure Machine Learning, the following blog post is after a quizzing session to get understand how to get started with Azure Machine Learning" Each student receives $100 of Azure credit per month, for 6 months. The Faculty member receives $250 per month, for 12 months. The Azure machine learning team provided a very nice walkthrough tutorial which covers a lot of the basics. This tutorial is really useful as it takes you through the entire process of creating an AzureML workspace, uploading data, creating an experiment to predict someone's credit risk, building, training, and evaluating the models, publishing your best model as a web service, and calling that web service. Now you need to learn how to import a data set into Azure Machine Learning, and where to find interesting data to build something amazing.

Using Azure for Machine Learning – Microsoft Faculty Connection


In my spare time, I love learning new technologies and going to hackathons. Our hackathon project Pantrylogs using Artificial Intelligence was selected as one of the 10 Microsoft Imagine Cup UK finalists. I'm interested in learning more about AI, Data Science, and Machine Learning to improve the performances of our application. In this article, I would love to share my experience of using Azure Machine Learning Studio with you. Azure Machine Learning Studio is a very powerful browser-based, visual drag-and-drop authoring environment.

DEAP documentation -- DEAP 1.1.0 documentation


DEAP is a novel evolutionary computation framework for rapid prototyping and testing of ideas. It seeks to make algorithms explicit and data structures transparent. It works in perfect harmony with parallelisation mechanism such as multiprocessing and SCOOP. The following documentation presents the key concepts and many features to build your own evolutions.