Finally! Bayesian Hierarchical Modelling at Scale

For a long time, Bayesian Hierarchical Modelling has been a very powerful tool that sadly could not be applied often due to its high computations costs. With NumPyro and the latest advances in high-performance computations in Python, Bayesian Hierarchical Modelling is now ready for prime time.

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Honey, I shrunk the target variable

Feature engineering takes up a huge part in the work-life of a data scientist. Sometimes this doesn’t stop at features but also the target variable itself is transformed leading to all kinds of unexpected consequences. In this post, you will learn about common pitfalls, how a transformation can affect the error measure, the math behind it, and even how all this can be used to your advantage.

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Are you sure about that?! Uncertainty Quantification in AI

With the advent of Deep Learning (DL), the field of AI made a giant leap forward and it is nowadays applied in many industrial use-cases. Especially critical systems like autonomous driving, require that DL methods not only produce a prediction but also state the certainty about the prediction in order …

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Multiplicative LSTM for sequence-based Recommenders

Recommender Systems support the decision making processes of customers with personalized suggestions. They are widely used and influence the daily life of almost everyone in different domains like e-commerce, social media, or entertainment. Quite often the dimension of time plays a dominant role in the generation of a relevant recommendation.

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