You are viewing content from a past/completed QCon - November 2020

Machine Learning for the Software Engineer

Discover what it takes to start and deploy a machine learning project. We cover the machine learning pipeline by looking at data collection, model training, and model deployment. Training a machine learning model is just the tip of the iceberg of a successful project. In this track we will also look at how to set up a data collection process, and what features to select for your own project. We will answer practical questions of software engineers, among which “but how do I deploy this trained model now”, and “why does it take so long to train my model”. We will also cover what machine learning models to train, and what the latest machine learning techniques are that you have to apply to get good scores on ML benchmarks.


Roland Meertens

Product Manager @annotell
Roland has a passion for Artificial Intelligence, and is specialised in robotics projects. He set up machine learning projects all the way from sensor selection, data collection and labelling to deploying the model in production. Please approach him to talk about deep learning and neural networks. Read more

Tuesday Nov 10 / 12:00PM EST


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