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Why we love numpy 100 000 term frequency vs inverse doc frequency
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Classroom Contents
Scientist Meets Web Dev - How Python Became the Language of Data
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- 1 Intro
- 2 Data science with Python is hot
- 3 We're different
- 4 Let's do something together: sort EuroPython site EuroPyton abstracts
- 5 Why we love numpy 100 000 term frequency vs inverse doc frequency
- 6 arrays are nothing but pointers A numpy array
- 7 Array computing is fast
- 8 Array computing is limited by CPU starvation
- 9 Numerics versus control flow What if there is an if
- 10 numerics vs databases
- 11 Operations on chunks Machine learning, data mining = numerics
- 12 Operations on chunks, or algorithms on chunks Machine learning, data mining = numerics
- 13 Making the data-science magic happens
- 14 Data/computation flow is crucial
- 15 Ingredients for future data flows
- 16 The Python VM is great
- 17 Scikit-learn is easy machine learning As easy as py
- 18 Difference is richness, but requires outreach
