Start by making your code reusable, then look at tooling


MLOps is one if the most popular buzzwords in Machine Learning and Data Science at the moment, but one of the areas least covered by online courses, YouTube videos and bootcamps.

You can read up on how I define MLOps at home here:

Since writing the above article, I have…

TabNet balances explainability and model performance on tabular data, but can it dethrone boosted tree models?

TabNet model architecture. How does TabNet work?


Gradient Boosting models such as XGBoost, LightGBM and Catboost have long been considered best in class for tabular data. Even with rapid progress in NLP and Computer Vision, Neural Networks are still routinely surpassed by tree-based models on tabular data.

Enter Google’s TabNet in 2019. According to the paper, this…

And why you need to know about it…

Linear Model vs Generalised Additive Model


Linear Models are considered the Swiss Army Knife of models. There are many adaptations we can make to adapt the model to perform well on a variety of conditions and data types.

Generalised Additive Models (GAMs) are an adaptation that allows us to model non-linear data while maintaining explainability.

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Adam Shafi

Data Scientist | Get in touch:

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