Other than being one of the leading cloud providers in the AWS has been one of the leading names in the rise of AI and ML. Amazon has been AI adn ML for pricing in its e-commerce site and it has been used in the banking and finance industry since the 90s to analyse risk.
AWS has one of the widest range of AI and ML products and services within their cloud services. Below are some of AWS’s ML and AI products made for companies who wish to leverage all AI and ML benefits for their products and services.
Amazon SageMaker is a fully managed service which helps developers and data scientists with the ability to build, train and deploy machine learning models. What makes ML difficult and complex is its place among the software development lifecycle. SageMaker can help developers and data scientists to incorporate ML into every step of the software development. So instead of developers and data scientists needing to incorporate different tools in different phases on the software development lifecycle, they can simply use Amazon SageMaker for all their needs. SageMaker comes with multiple tools which help to incorporate ML into the software development lifecycle easily.
Amazon SageMaker Studio
As the name suggests, Amazon SageMaker Studio is a web-based interface where ML development can be done. Amazon SageMaker Studio gives developers and data scientists the complete control to build, train and deploy models. All activities from creating models, debugging, model drift detection and automatic model creation.
Amazon SageMaker Studio Notebooks
When it comes to working ML development, you will be working with multiple developers and data scientists, with Amazon SageMaker Studio Notebooks you and your team can be on the same page. There are also multiple pre-built notebooks with different test cases for it will easy to document the process as well.
Amazon SageMaker Autopilot
Amazon SageMaker Autopilot is the industries first machine learning automation to control of all your ML development activities. For example, when creating an ML model, developers and data scientists usually have a compromise between accuracy and low latency, tweaking these metrics for the best output is difficult, but with Amazon SageMaker Autopilot you will get the best output by executing the raw data with algorithms at fraction of the time if done manually. Amazon SageMaker Autopilot has a low learning curve as well so your developers and data scientists can be up and running at a quick pace.
Amazon SageMaker Ground Truth
Good ML development needs data, heaps and heaps of data. The data has to be carefully segregated into different metrics to maintain an accurate dataset. The databases have to be updated, accurately separated and labelling them. These above-mentioned tasks are time-consuming, complicated and expensive. No one wants their developers and data scientists working maintaining datasets instead of developing ML algorithms, Amazon SageMaker Ground Truth can learn from how the datasets are created, labelled, separated and learn to build datasets from raw data on its own.