The Machine Learning Process in 7 Steps
In this article, I describe the various steps involved in managing a machine learning process from beginning to end. Depending on which company you work for, you may or may not be involved in all the steps. In larger companies, you typically focus on one or two specialized aspects of a project. In small companies, you may be involved in all the steps. Here the focus is on large projects, such as developing a taxonomy, as opposed to ad-hoc or one-time analyses. I also mention all the people involved, besides machine learning professionals.
Steps involved in machine learning projects
In chronological order, here are the main steps. Sometimes it is necessary to recognize errors in the process and move back and start again at an earlier step. This is by no mean a linear process, but more like trial and error experimentation.
Read the full article here, discussing the 7 steps, from defining the problem to maintenance.
Analytics consultant, educator, adventure scientist/explorer || MN’23 The Explorers Club
3 年Steps 6 and 7 critical and often downplayed in importance.
Leading authority on Digital Decisioning and delivering business impact from AI and machine learning
3 年Vincent Granville I was very disappointed in the first couple of steps - Defining the problem and Defining goals are opportunities to be business-centric. They are about defining business needs and business metrics, finding the business decision that must be improved. Jumping straight into talking about data and cloud architectures and types of analyses is what most data science teams do and results in projects that can't make it out of pilot or POC. These first steps must be focused on the business and its decision-making problem and teams would be well served not to ask any of the questions you list until AFTER they know how the business sees the problem. Otherwise they're just going to be another group of nerdy data scientists off playing with their data and adding no business value.
Enthusiastic about AI/ML driven innovation and digital transformation
3 年Great article.! discussing costs, ROI and timeframe should be emphasized more... Many either disregard or lack knowledge on financial analysis of the analytics effort...