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?”
Luckily we can help. 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.
The emphasis is on practicaltiy, and this applies right across our speaker lineup. You’ll find a wealth of practical examples of how practioners have addressed key challenges, whether it;s scaling up machine learning at Adobe, bridging the gap between machine learning and analytics at Babbel, or using predictive analytics in test management.
We’ll be getting even deeper, at our four highly practical workshops covering topics including: developing and deploying Neural Nets; text mining; developing with TensorFlow 2; and getting machine learning into production using containers and DevOps.
This will all be taking place at the QE II Conference Center, in London, England, from September 30 to October 2, and as usual there will be excellent food right the way through. So to bag your spot, head over to the MCubed website now, and we’ll see you in September. ®
Balancing consumerization and corporate control
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