The Machine Learning Pipeline on AWS course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment.
The Machine Learning Pipeline on AWS course explores how to use the machine learning (ML) pipeline to solve a real business problem in a project-based learning environment.
Students will learn about each phase of the pipeline from instructor presentations and demonstrations and then apply that knowledge to complete a project solving one of three business problems: fraud detection, recommendation engines, or flight delays. By the end of the course, students will have successfully built, trained, evaluated, tuned, and deployed an ML model using Amazon SageMaker that solves their selected business problem.
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Accelebrate's  Machine Learning with TensorFlow & Keras training teaches attendees how to develop real-world machine learning applications powered by TensorFlow and Keras, popular technologies for building production-grade deep learning models. Students also learn how to use an HTTP API to retriev...
Why write programs when the computer can instead learn them from data? In this class you will learn how to make this happen, from the simplest machine learning algorithms to quite sophisticated ones.
[AI INTRO] is a math heavy course offered at KTBYTE, and require students to have mastered self-guided learning.
This course provides an introduction to machine learning, the study of systems that improve automatically based on data and past experience
This 35-hour Machine Learning with R course introduces both the theoretical foundation of machine learning algorithms as well as their practical applications in R.
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