Six Success Factors for Getting Started with Machine Learning There is a wide range of ML use cases that can help organizations grow. However, the technology is still primarily in the early mainstream adoption stage. Read this TDWI Checklist Report to learn key best practices for getting started with AI/ML and making it work across your enterprise. Six Success Factors for Getting Started with Machine Learning There is a wide range of ML use cases that can help organizations grow. However, the technology is still primarily in the early mainstream adoption stage. Read this TDWI Checklist Report to learn key best practices for getting started with AI/ML and making it work across your enterprise.

Agricultural fields are no less than a battlefield. Irrespective of terrain, geography and type, crops have to compete against scores of different weeds, species of hungry insects, nematodes and a broad array of diseases. Weeds, or invasive plants, aggressively compete for soil nutrients, light and water, posing a serious threat to agricultural production and biodiversity. Weeds directly and indirectly result in tremendous losses to the farm sector, which convert to billions each year worldwide. To combat these challenges, the farm sector is looking at Artificial Intelligence (AI) based solutions.