If you’re considering implementing machine learning in your software product, you’ll find many reasons to do so.
There are multiple reports on what organizations and humans can achieve with machine learning. Moreover, big companies such as Amazon have improved their products, gained business insights, and recorded remarkable results with machine learning models.
But successful machine learning implementation requires a solid understanding of what it entails and proper management of machine learning projects. Unfortunately, most of the available resources on machine learning only cover the technical aspects.
Unless you’re not a savvy programmer, you may struggle to understand what machine learning really is and when you need it.
To help you work around the issue, we wrote this article based on a two-part webinar we’d hosted with two machine learning specialists who talked extensively about machine learning implementation: Łukasz Grzybowski and Willy Picard.
Read on to learn: