Perhaps one of the most difficult steps in building a machine learning model is choosing the first set of hyperparameters. This will pariticularly be challenging in the case of neural networks and deep learning models, where we need to decide about several haperparameters during the building the first model. Here, in this post, I will list my favorite blog posts, research papers, and maybe textbook pages providing practical guide or useful suggestions for constructing the version 1.0 of machine learning and deep learning models.

Last update: October 2021

  1. An executive’s guide to AI
  2. Deep Learning Rules of Thumb
  3. Cookbook
  4. Rules-of-thumb for building a Neural Network