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Ludwig: A Code-Free Deep Learning Toolbox
Piero Molino introduces Ludwig, a deep learning toolbox that allows to train models and to use them for prediction without the need to write code.
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Deep Learning on Microcontrollers
Pete Warden discusses why Deep Learning is a great fit for tiny, cheap devices, what can be built with it, and how to get started.
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Open Banking - Tales from the Frontier
Anca Zaharia and Jason Maude focus on the successes and pitfalls Starling Bank encountered in building Open Banking. Topics covered: the OAuth security flow, the permissions-controlled API, and more.
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Powering Flexible Payments in the Cloud with Kubernetes
Ana Calin covers the technical and security challenges Paybase faced and the lessons they learned as they built their cloud-native microservices architecture and integrated with traditional systems.
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Panel: Bleeding Edge at Hyperspeed with No Breaks and No Breaches
The panelists talk about the risks of continuous deployment, how to be safe and secure when releasing many times a day or how to convince regulators, auditors and customers.
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Change Is the Only Constant
Stuart Davidson talks about real-world examples from Skyscanner where he thinks the decisions they've made have helped them deal with change and which might be interesting to a technical audience.
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Corda: Looking Forward and Back, Blockchain on a JVM Stack
Carolyne Quinn and Mike Ward discuss Corda, an open source enterprise blockchain, and look at technologies used: Kotlin, JVMs, pluggable consensus, Corda Foundation and SGX,.
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Practical NLP for the Real World
Emmanuel Ameisen discusses examples of how to build practical applications using NLP, diving into data visualization and labelling, as well as model validation.
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Federated Learning: Rewards & Challenges of Distributed Private ML
Eric Tramel discusses the basic concepts underlying the federated ML approach, the advantages it brings, as well as the challenges associated with constructing federated solutions.
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Michelangelo Palette: A Feature Engineering Platform at Uber
Amit Nene and Eric Chen discuss the infrastructure built by Uber for Michelangelo ML Platform that enables a general approach to Feature Engineering across diverse data systems.
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Instrumentation, Observability & Monitoring of Machine Learning Models
Josh Wills discusses the monitoring and visibility needs of machine learning models in order to bridge gaps between ML practitioners and DevOps.
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Habito: The Purely Functional Mortgage Broker
Will Jones talks about Haskell at Habito, some of the wins and trade-offs. He also talks about why functional programming is beneficial for large projects, and with migrating a data store.
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