The edge machine vision sector is growing rapidly, but developers must have access to the right hardware if they are to keep up with demand and stay ahead of their competitors. Inadequate technology is a formidable barrier to progress, with developers being forced to either create their own MV cameras or try to integrate complex MV cameras into the systems they’re developing. But off the shelf, ‘plug and play’ cameras could provide the ideal solution to keeping progress moving - allowing develop

Main Challenges in Machine Learning: 1. Insufficient or Poor-Quality Data Lack of labeled data for supervised learning. Noisy, incomplete, or biased data can lead to poor models. 2. Overfitting and Underfitting Overfitting: Model performs well on training data but poorly on new data. Underfitting: Model is too simple to capture the underlying pattern. 3. High Computational Cost Training complex models (e.g., deep learning) requires powerful hardware and GPUs. 4. Scalability Models trained on sma