How does cloud computing integrate with AI and machine learning projects?

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Cloud computing plays a huge role in AI and ML projects by providing the necessary infrastructure to run complex models and store large datasets. Here’s how they work together:

  • Scalability: Cloud platforms provides powerful computing resources that can scale up or down based on the demands of AI and ML models. This allows data scientists to train models faster without worrying about hardware limitations.
  • Storage: AI and ML require huge datasets. Cloud storage provides a secure and cost-effective way to store and access data from anywhere.
  • Tools and Services: Cloud providers like AWS, Azure, and Google Cloud provide ready-made AI and ML tools, such as TensorFlow, PyTorch, and AutoML, which make it easier for teams to develop and deploy machine learning models without deep technical expertise.

By using the cloud, AI and ML projects can be run more efficiently, cost-effectively, and at a larger scale.