A Machine Learning Text Classification Case Study with a Product-driven Twist
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This is a machine learning case study with a product-driven twist: we’re going to pretend we have an actual product we need to improve. We will explore a dataset and try out different models like logistic regression, recurrent neural networks, and transformers, looking at how accurate they are, how they are going to improve the product, how fast they work, and whether they're easy to debug and scale up.