What Developers Need to Know About Machine Learning in the SDLC - DZone AI

To learn about the current and future state of machine learning (ML) in software development, we gathered insights from IT professionals from 16 solution providers. We asked, "What do developers need to keep in mind when using machine learning in the SDLC?" Here's what we learned: The biggest issue for ML is viewing it as an omnipotent savior of the SDLC, thereby negating the need to adhere to traditional SDLC design and protocol. ML can greatly improve efficiency and allow developers to better allocate their time to actions that require human input. It cannot, however, completely take the place of conscientious, diligent and thoughtful software planning, design, development, and version control. Use the tools provided by public cloud providers. They are self-paced, painless, and you can get certified.