ML Cost

#Difficulty of the Problem

• Do we have ready made ML solutions (libraries, systems)?
• Depending on the problem, which type of algorithms do we need to design/implement (classification, regression, Clustering, or [[Y2Q2/Machine Learning Foundations/Introduction/Reinforcement Learning]]) and how difficult is it to implement/deliver/maintain?

#Cost of the Data

• Can data be generated automatically?
• What is the cost of manual annotation of the data?
• How many examples are needed? Cannot be known in advance, but can be estimated from known published results or the organization’s knowledge.

#Need for Accuracy

• Cost grows super-linearly with the accuracy requirement.
• How costly is each wrong prediction?
• What is the lowest tolerable accuracy level below which the model becomes impractical?