Chandu Chilakapati and Devin Rochford, Alvarez & Marsal
Machine Learning Accuracy Assessment and How to Improve Outputs
Those who trust too much and those who don’t trust machine learning enough will both miss out on potentially better accuracy.
Understanding and Assessing Machine Learning Algorithms
Knowing the types of algorithms and what they accomplish can help finance executives ask the right questions when working with data.
Selecting and Preparing Data for Machine Learning Projects
Data is the foundation of any machine learning model. Here's how to deal with bias, cross-contamination, and non-numeric inputs.