When it comes to developing intelligent solutions, one of the biggest questions businesses face is whether to run their projects in the cloud or keep them on local infrastructure. This decision is especially important if you’re working with a machine learning development company or building your own machine learning models . Both approaches have their strengths, and understanding them can save you time, money, and headaches in the long run. Cloud-Based Machine Learning – The Modern Favorite Cloud platforms like AWS, Azure, and Google Cloud have transformed how teams build and deploy machine learning models. A machine learning development company working in the cloud gains immediate access to scalable computing power, ready-to-use tools, and flexible storage. You pay for what you use, which makes it easier to start small and grow as your needs expand. Pros of Cloud-Based ML: Scalability on demand: You can train massive models without buying expensive hardware. Access to advanced tools:...