Friday, 24 March, 2023

ML-Ops: ML and AI also need agility in spite of ‘self-learning’ capabilities

<p>Agile SD approach employs DevOps strategy for the speedy delivery of products. ML processes lifecycle, due to its &lsquo;self-learning&rsquo; capabilities, remains unattended. ML-Ops emphasises on agile development in ML covering stages like data acquisition, cleansing, model development etc. An active feedback mechanism monitors performance (precision, recall, accuracy) and alerts ML-Ops teams on the need to update the models when there is a data or concept drift.</p>