Continuous integration applied to machine learning, in under twenty minutes.
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1 lesson, 8 minutes
An eight-minute introduction to machine learning: how a model learns from data, the difference between supervised and unsupervised learning, and where each is used.
24 hours
Forty-four lessons covering the statistics behind machine learning, from sampling to hypothesis testing and interview questions.
13 minutes
What machine learning is, explained without the mathematics, in thirteen minutes.
13 minutes
Thirteen minutes on how a model is judged, and why accuracy alone is rarely the answer.
45 minutes
Forty-five minutes of scikit-learn, from fitting a model to scoring it.
5 hours
Five hours on MLOps: getting a model out of a notebook and keeping it running.
5 hours
Five hours on MLOps: getting a model out of a notebook and keeping it running.
