Description

“No code” machine studying (ML) refers to using ML platforms, instruments, or libraries that permit customers to construct and deploy ML fashions with out writing any code. This method is meant to make ML extra accessible to a wider vary of customers, together with those that could not have a powerful programming background.

Amazon SageMaker is a completely managed machine studying service supplied by Amazon Net Companies (AWS) that permits builders and information scientists to construct, practice, and deploy machine studying fashions at scale. SageMaker additionally contains built-in algorithms, pre-built libraries for frequent machine studying duties, and quite a lot of instruments for information pre-processing, mannequin tuning, and mannequin deployment. SageMaker additionally integrates with different AWS companies to supply a whole machine studying setting.

AutoML in SageMaker refers back to the automated choice and tuning of machine studying fashions to enhance the accuracy and efficiency of the fashions. This may be achieved by utilizing SageMaker’s built-in algorithms and libraries or by utilizing customized algorithms and libraries. SageMaker additionally features a function known as Computerized Mannequin Tuning which permits for tuning of the hyper-parameters of the fashions to enhance their efficiency.

SageMaker Studio Canvas is a function that permits customers to work together with their information, construct and visualize workflows, and create, run, and debug Jupyter notebooks, all inside the similar web-based interface. The Canvas offers a visible and interactive solution to discover, manipulate and visualize information, and permits customers to create Jupyter notebooks and drag-and-drop pre-built code snippets, known as “recipes” to shortly carry out frequent information pre-processing, information visualization, and information evaluation duties.

SageMaker Studio Canvas additionally permits customers to simply share their notebooks, recipes, and information with different customers and collaborate on tasks. This helps to simplify the machine studying improvement course of, speed up the event of machine studying fashions, and enhance collaboration amongst groups.

IN THIS COURSE YOU WILL LEARN :

  • LifeCycle of a Machine Learning Challenge

  • Machine Learning Fundamentals

  • Cloud Computing for Machine Learning

  • AWS SageMaker Canvas (NO CODE ML)

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