As companies mature through their Machine Learning journey, a pattern of “many models” often emerges. In the real world, many problems can be too complex to be solved by a single machine learning model. Whether that be predicting sales for each individual store, building a predictive maintenance model for thousands of oil wells, or tailoring an experience to individual users, building a model for each instance can lead to improved results on many machine learning problems, as opposed to training a single model to make predictions for all instances. However, the infrastructure, procedures and level of automatization required to operate this kind of pattern poses a challenge at all levels.
#BIGTH20 #MLOps #DevOps
Session presented at Big Things Conference 2020 by María Medina, Senior Data Scientist at Microsoft and Hosein Alizadeh, Principal Data Scientist at Microsoft
18th November 2020
Do you want to know more? https://www.bigthingsconference.com/