Preparing Training Data

One of the major tasks in training machine learning (if not the major-task) is preparing the training data. This is a tedious task that requires people who like repetitive work. Though it is tedious, it is (in our opinion) even more important than knowing which model to use, what software to write to train the system.

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Keras2-based WaveNet published on GitHub

At Munich Artificial Intelligence Laboratories (M-AILABS), we experiment with a lot of technologies and methods. We also look for novel ways of doing things in the area of ML & AI.

One of my personal dreams is to have an AI-based solution that can “compose” music. And of course, it has to be music like the great Ludwig van. So, we started looking for some papers.

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Presentation at the M3-Conference in Cologne, April 2018

In 2018 the M3-Conference (Minds Mastering Machines) is held in Cologne between April 25th-26th.

Munich Artificial Intelligence Laboratories (M-AILABS) will be talking about “ML & AI: From algorithms to practical implementation” about the challenges, pitfalls and tasks from the moment of deciding to employ ML/AI until it can actually be trained (and hopefully deployed).

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