Explain machine learning and how is cloud important?

Question

Accepted Answer

Machine learning is a branch of AI that enables computers to learn and make predictions without explicit programming.

Machine learning is a subset of artificial intelligence (AI) that focuses on developing algorithms and models that allow computers to learn from and make predictions or decisions based on data.
It involves training a model on a large dataset and using it to make predictions or decisions on new, unseen data.
Cloud computing is important for machine learning as it provides the necessary infrastructure and resources to store and process large amounts of data, train complex models, and deploy them at scale.
Cloud platforms like Amazon Web Services (AWS) and Google Cloud Platform (GCP) offer machine learning services and tools that make it easier to develop, train, and deploy machine learning models.
Cloud-based machine learning allows for scalability, flexibility, and cost-effectiveness, as resources can be easily scaled up or down based on demand.
For example, companies can use cloud-based machine learning to analyze customer data and make personalized product recommendations, detect fraud in real-time, or automate repetitive tasks.
Cloud also enables collaboration and sharing of machine learning models and datasets across teams and organizations.
Overall, cloud computing plays a crucial role in enabling the development, deployment, and scalability of machine learning applications.

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