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🌲 Machine Learning in Agriculture: Scaling AI for Crop Management with Dror Haor
In this episode, Dean speaks with Dror Haor, CTO at SeeTree, about the challenges of deploying AI in agriculture at scale. They explore how SeeTree integrates AI and sensor fusion to manage vast amounts of remote sensing data, helping farmers improve crop yields with high accuracy at low costs. Dror shares insights on handling data drift, customizing models for different regions, and balancing the trade-offs between cost and performance. This conversation dives deep into practical machine learning applications in agriculture, offering valuable lessons for anyone working with large-scale data and AI.
Join our Discord community: https://discord.gg/tEYvqxwhah
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Timestamps:
00:00 Introduction
00:32 Production in machine learning at SeeTree
07:34 Sensor fusion in machine learning
16:26 Balancing accuracy and cost in agriculture
20:09 Customizing models for different customers and crops
24:19 Dealing with data in different domains
30:10 Tools and processes for ML at SeeTree
35:58 Building for scale
40:17 Collecting user feedback and self-improving products
42:45 Exciting developments in ML & AI
45:12 Hot takes in ML - Overfitting is good
46:34 Recommendations for the Audience
➡️ Dror Haor on LinkedIn – https://www.linkedin.com/in/dror-haor-phd-77152322/
➡️ Dror Haor on Twitter – https://x.com/DrorHaor
🌐 Check Out Our Website! https://dagshub.com
Social Links:
➡️ LinkedIn: https://www.linkedin.com/company/dagshub
➡️ Twitter: https://x.com/TheRealDAGsHub
➡️ Dean Pleban: https://x.com/DeanPlbn
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By Dean Pleban @ DagsHubIn this episode, Dean speaks with Dror Haor, CTO at SeeTree, about the challenges of deploying AI in agriculture at scale. They explore how SeeTree integrates AI and sensor fusion to manage vast amounts of remote sensing data, helping farmers improve crop yields with high accuracy at low costs. Dror shares insights on handling data drift, customizing models for different regions, and balancing the trade-offs between cost and performance. This conversation dives deep into practical machine learning applications in agriculture, offering valuable lessons for anyone working with large-scale data and AI.
Join our Discord community: https://discord.gg/tEYvqxwhah
---
Timestamps:
00:00 Introduction
00:32 Production in machine learning at SeeTree
07:34 Sensor fusion in machine learning
16:26 Balancing accuracy and cost in agriculture
20:09 Customizing models for different customers and crops
24:19 Dealing with data in different domains
30:10 Tools and processes for ML at SeeTree
35:58 Building for scale
40:17 Collecting user feedback and self-improving products
42:45 Exciting developments in ML & AI
45:12 Hot takes in ML - Overfitting is good
46:34 Recommendations for the Audience
➡️ Dror Haor on LinkedIn – https://www.linkedin.com/in/dror-haor-phd-77152322/
➡️ Dror Haor on Twitter – https://x.com/DrorHaor
🌐 Check Out Our Website! https://dagshub.com
Social Links:
➡️ LinkedIn: https://www.linkedin.com/company/dagshub
➡️ Twitter: https://x.com/TheRealDAGsHub
➡️ Dean Pleban: https://x.com/DeanPlbn