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Machine Learning 101

Translations: en

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#11 PyData Warsaw

This talk is about the basics of Machine Learning and Deep Learning. We will cover the basics of Supervised and Unsupervised Learning with examples of different models used for each one. I will highlight how you can use scikit-learn to use these models and cases where they won't work. With this background, we will move onto how neural networks work and basics of Convolutional Neural Networks (CNNs) used in image classification. At the end of the talk, you will be able to explain how different models work and make the right choice for your use case.

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