The Cold Start Problem
You might sometimes find that it's hard to get started doing something, but once you're going, it gets easier. Turns out machine learning algorithms, and especially recommendation engines, feel the s...
26 Syys 201615min
Open Source Software for Data Science
If you work in tech, software or data science, there's an excellent chance you use tools that are built upon open source software. This is software that's built and distributed not for a profit, but ...
19 Syys 201620min
Scikit + Optimization = Scikit-Optimize
We're excited to welcome a guest, Tim Head, who is one of the maintainers of the scikit-optimize package. With all the talk about optimization lately, it felt appropriate to get in a few words with s...
12 Syys 201615min
Two Cultures: Machine Learning and Statistics
It's a funny thing to realize, but data science modeling is usually about either explainability, interpretation and understanding, or it's about predictive accuracy. But usually not both--optimizing ...
5 Syys 201617min
Optimization Solutions
You've got an optimization problem to solve, and a less-than-forever amount of time in which to solve it. What do? Use a heuristic optimization algorithm, like a hill climber or simulated annealing-...
29 Elo 201620min
Optimization Problems
If modeling is about predicting the unknown, optimization tries to answer the question of what to do, what decision to make, to get the best results out of a given situation. Sometimes that's straigh...
22 Elo 201617min
Multi-level modeling for understanding DEADLY RADIOACTIVE GAS
Ok, this episode is only sort of about DEADLY RADIOACTIVE GAS. It's mostly about multilevel modeling, which is a way of building models with data that has distinct, related subgroups within it. What...
15 Elo 201623min
How Polls Got Brexit "Wrong"
Continuing the discussion of how polls do (and sometimes don't) tell us what to expect in upcoming elections--let's take a concrete example from the recent past, shall we? The Brexit referendum was, ...
8 Elo 201615min
