Pattern Recognition and Machine Learning

A quick book recommendation for those trying to strengthen their machine learning knowledge:  Christopher Bishop’s Pattern Recognition and Machine Learning.  I have found it incredibly helpful in adding depth to sources like Andrew Ng’s Coursera class.  It’s apparently a staple in the Computer Science world, but I was never exposed having come from physics.

The topics you would expect are there with great depth and clarity.  However, it is also focused on providing the Bayesian perspective.  If you’re new to Bayesian ideas applied to Machine Learning this is an excellent text.  It does a great job of both contrasting frequentist vs Bayesian approaches and showing their connections.  It should be on every Data Scientist’s shelf.

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