Interleaving a Human/ Machine learning Technique

Interleaving in Human learning

What is interleaving?

  • Discriminative contrast: Mixing materials helps learners notice the similarities and differences between the concepts they are learning which helps them learn the concepts better.
  • Another notable mechanism behind interleaving is that it pushes learners to figure out what strategies, techniques, and information they need to use in order to solve problems that they encounter.

Interleaving in Machine learning

Similarly to the concept behind interleaving in human learning, Netflix uses interleaving technique to accelerate the pace of algorithm innovation by increasing the rate of learning which to leads to even more personalized , hence better recommendations.

Conclusion

Just like in both human and machine learning, interleaving can be a powerful technique for more productive learning process. In Machine learning, this technique is used to accelerate ranking algorithm innovation at Netflix. It allows them to sensitively measure member preference for ranking algorithms and to identify the most promising candidates within days. This has enabled them to quickly test a broad set of new algorithms, and thus increase their rate of learning.

Data Scientist