A high-level overview of managing a machine learning project in your company.
Alright, so you have identified a problem where machine learning is the appropriate solution. You are now probably considering how you can bring your idea to reality. I am hoping to give you a brief ‘how-to’ guide to getting the most value out of your project.
Let me start by identifying the key components of a successful machine learning project and then I will briefly describe each step in more detail.
- Success Metrics
A machine learning project can be complex and daunting. You will need a team with diverse technical and business skills.
You are definitely going to need technically talented engineers to build it but they should not be your first hires.
Your very first hire should be a business person who will run the project. The business person will provide context to your problem and ensure that whatever you build delivers value to the business. While some understanding of machine learning is needed, your first hire does not need a Ph.D. Your first hire will serve as the champion of the project and will be responsible for its outcomes.
Only after you have your champion should you hire engineers.