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A few weeks ago, we revealed how Dailymotion’s data scientists and data engineers collaborate to efficiently release into production, but how does this change impact our day-to-day life as data scientists? Does it offer enough flexibility to break the new in artificial intelligence? The answer is yes! Here are some pointers on how to conduct a project which fits our machine learning automation pipeline while tackling a technical issue, namely ingesting sparse inputs in Keras.

One of the challenges we face as a multinational company is having complete knowledge of our video catalog while being efficient both in terms of computation time and costs. This means that important products developed by the Dailymotion Data & AI team are related to video characterization. We are constantly asking ourselves how we can optimize the process in order to reduce our costs in storage, training, etc. …

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