Deploying models (to tractors 🚜)
Practical AI
Deploying ML in Agriculture
This chapter explores the challenges and strategies for deploying machine learning models in agricultural settings, emphasizing real-time data processing and the need for multiple adaptive models. It also discusses the importance of MLOps practices, model retraining, and performance evaluation metrics for effective agricultural applications.
00:00
Transcript
Play full episode
Remember Everything You Learn from Podcasts
Save insights instantly, chat with episodes, and build lasting knowledge - all powered by AI.
