Deploying Machine Learning Models (is still terrible)

Designing, building, and training models are hard problems. Literature is reviewed, data is gathered (and cleaned and annotated). Hours (or perhaps days? weeks?) are spent getting code to work, fixing subtle bugs, tuning training schemes. Finally, the met… Read more


Statistics for Machine Learning: Resources

People who come to machine learning/data science from a software engineering background (as opposed to a scientific or statistical background) often gloss over the statistical underpinnings of many machine learning methods. This is fine initially when you... (more…)

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