If you want to put machine learning to work in your organisation, you should really consider securing a place at one of the four all-day workshops we're running as part of MCubed before our early bird ticket offer expires in two weeks time. Oliver Zeigermann returns to take you through the basics of machine learning, before diving into neural networks and deep learning and working up to convolutional neural networks, all using TensorFlow and sklearn. To learn how to build basic models and crucially get them into production in the real world, join Terry McCann for his workshop on "From model to production using the cloud, Containers and Devops". As well as using Python to develop models, this highly interactive session will show how to exploit common technologies such as Azure, Docker and Kubernetes. For a holistic, soup to nuts introduction to machine learning, join Prof Mark White and Kate Kilgour.
Events Even if news coverage of machine learning and AI leaves you wondering whether to laugh or cry, you know these technologies are going to profoundly change your organisation as either you adopt them or your partners and rivals do. That's why the agenda at MCubed next month will show you how to get to grips with the technology, apply it to the problems you face in your business or organisation and plan for the unexpected – whether it's security problems, privacy issues, or bias in training data. So in addition to our distinguished keynote speakers Dr Joanna Bryson and Professor Dagmar Monett Diaz, we've got speakers like Chris Knight demystifying machine learning, and Tesco alum Kate Kilgour rehearsing the basic maths underpinning it. We have in-depth examinations of key tools and techniques such as TensorFlow, Keras and Lime. Getting even more practical, we have Isabel Sargent leading a trio of speakers from the ONS talking about their use of deep learning in landscape mapping, Sören Klemm on making neural networks work when there are minimal resources available, and Ingo Elsen on applying machine learning to predicting train delays at Deutsche Bahn.
Event If you're thinking about doing machine learning, one of the first choices you'll have to make is "what will I actually run on my machines?" At MCubed, brought to you by The Register and Heise, our speakers will cover key tools and frameworks, showing you how to get up and running, and if you're ready, taking you right to the edge of what's possible. So, if you're looking to nail down the basics with TensorFlow, David Tyler will get you started. If you want to experiment with TensorFlow in the browser, check out this session from Oliver Zeigermann, while Lars Gregori will take you through embedded and edge applications. Likewise, IAV's Fabian Bormann will both introduce PyTorch and show how to migrate existing projects to it, while Datanizing's Christian Winkler will examine the role of mutliple text mining techniques, including word2vec, GloVe, fastText, ELMo and BERT And we'll even consider whether some frameworks are past their prime, with IAV's Sara Bartram.
Events Machine learning and artificial intelligence have moved out of the realms of academia into the world of real business – and the myriad applications and platforms that implies. You can develop and run models on massively complex data-rich systems, just like the most lavishly funded academics, or get by with sparse data and crimped hardware resources, even running your models on mobile or edge devices. Which is why the speaker lineup at our MCubed conference spans a wide range of industries, applications and form factors, highlighting how businesses like yours can experiment with and exploit the technology. So in addition to our distinguished keynote speakers, Dr Joanna Bryson and Professor Dagmar Monett Diaz, we've got SAP's Lars Gregori showing you how to integrate machine learning models into iOS and Android applications and devices. At the other end of the mobile scale, we have Abaco's Ross Newman discussing how GPUs are being used in military vehicles to enable AI-powered, real-time vision systems.
Laurent is a Senior Research Associate at the University of Cambridge, where his work focuses on the development and application of machine learning methods to understand high throughput biological data. Alternatively, Barbara Fusinska will be doing an all-day session on Practical Deep Learning with TensorFlow. Using an interactive learning platform, attendees will have a practical opportunity to use TensorFlow when building deep networks, training them and evaluating the results. After two days of conference sessions, either workshop is an excellent opportunity to dive deep on the fundamentals of machine learning and deep networks.