Causality in Machine Learning
Diogo shares his journey in tackling a Kaggle competition, emphasizing the importance of feature engineering in causality detection. By leveraging machine learning algorithms and fitting techniques, he dramatically increased the number of features used in his model. His unique approach allowed him to outperform competitors who relied on traditional statistical tests, achieving a significant edge in performance metrics.In this clip
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The TWIML AI Podcast (formerly This Week in Machine Learning & Artificial Intelligence)
Deep Learning: Modular in Theory, Inflexible in Practice with Diogo Almeida - #8
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