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Pragmatic Applications Series: Improving Churn Models


You are a machine learning engineer at a credit card company who is responsible for building a model to predict customer churn. After building your model, you will need to...

Pragmatic Applications: Detecting Fraud


Every year, fraud costs the global economy over $5 trillion. AI practitioners are on the front lines of this battle building and deploying sophisticated ML models to detect fraud, saving...

Pragmatic Applications: NLP Classification


From images and video to natural language and audio, unstructured data coupled with machine learning can unlock deeper AI potential and ROI for many organizations and use cases. Embeddings are...

Keeping Your Model In Production


So you have built and deployed your model into production – now what? Building a model and taking it from experimentation to production is hard — and keeping it there...