A grab-bag of Python patterns I reach for often when wrangling data and prototyping models.
1. Use list comprehensions wisely
This is paragraph 1. Data science work is part craft and part discipline — the best models are simple, well-validated, and easy to explain. In this post we walk through the intuition, the math just enough to be useful, and a clean implementation you can drop into your own pipeline.
This is paragraph 2. Data science work is part craft and part discipline — the best models are simple, well-validated, and easy to explain. In this post we walk through the intuition, the math just enough to be useful, and a clean implementation you can drop into your own pipeline.
This is paragraph 3. Data science work is part craft and part discipline — the best models are simple, well-validated, and easy to explain. In this post we walk through the intuition, the math just enough to be useful, and a clean implementation you can drop into your own pipeline.