What machine learning is, explained without the mathematics, in thirteen 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
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.
18 minutes
Continuous integration applied to machine learning, in under twenty minutes.
3 minutes
A 3-minute video from The Learning Studio.
7 hours
A seven-hour tutorial on probability and statistics for data science, from a Stanford PhD.
24 hours
Twenty-four hours of business analytics: the statistics, the tools and the reporting.
22 minutes
How categorical columns become numbers a model can use, and what goes wrong when they do not.
