AI/ML in AWS
In recent years, Machine learning (ML) has rapidly transitioned from a cutting-edge technology to a mainstream one. In the past, ML was primarily accessible to a select group of large tech companies and academic researchers. But with the advent of cloud computing, the resources required to work with ML, such as computing power and data, have become more widely available, enabling a wider range of organizations to utilize and benefit from ML technology.
ML has become an essential technology for many industries, and AWS is at the forefront of providing ML services to its customers. Some of the key trends in ML using AWS include:
- Serverless Machine Learning: AWS is making it easier to build, train, and deploy ML models without the need to manage servers. With services like Amazon SageMaker, customers can build and train models using managed Jupyter notebook instances and then deploy them to a serverless endpoint with just a few clicks.
- AutoML: Automating the model-building...
