As machine learning and artificial intelligence (AI) usher in the Fourth Industrial Revolution, everyone wants a piece. However, the machine learning process is complex and time-consuming, which discourages business analytics professionals and executives from being involved.
Enter, automated machine learning — created to automate the machine learning process. Automating the steps within machine learning is a game changer that empowers business analytics professionals and subject matter experts to uncover predictive insights and generate solutions to real-world problems without the need for programming or deep knowledge of algorithms.
- The 10 steps in the machine learning lifecycle, and the reason AI projects take weeks or months to complete (hint: it’s complex!)
- How automation improves each step of the current, manual machine learning process, delivering a reproducible process that is faster and with fewer errors
- Why automated machine learning enables data science for business analytics professionals, executives, and SMEs
- A checklist of features to look for when choosing an automated machine learning solution for your organization