AutoML Automated Machine Learning BootCamp (No Code ML)

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Price: 2999$

No code machine learning (ML) refers to the use of ML platforms, tools, or libraries that allow users to build and deploy ML models without writing any code. This approach is intended to make ML more accessible to a wider range of users, including those who may not have a strong programming background. Amazon Sage Maker is a fully managed machine learning service provided by Amazon Web Services (AWS) that enables developers and data scientists to build, train, and deploy machine learning models at scale. Sage Maker also includes built-in algorithms, pre-built libraries for common machine learning tasks, and a variety of tools for data pre-processing, model tuning, and model deployment. Sage Maker also integrates with other AWS services to provide a complete machine learning environment. Auto ML in Sage Maker refers to the automatic selection and tuning of machine learning models to improve the accuracy and performance of the models. This can be done by using Sage Maker’s built-in algorithms and libraries or by using custom algorithms and libraries. Sage Maker also includes a feature called Automatic Model Tuning which allows for tuning of the hyper-parameters of the models to improve their performance. Sage Maker Studio Canvas is a feature that allows users to interact with their data, build and visualize workflows, and create, run, and debug Jupyter notebooks, all within the same web-based interface. The Canvas provides a visual and interactive way to explore, manipulate and visualize data, and allows users to create Jupyter notebooks and drag-and-drop pre-built code snippets, called recipes to quickly perform common data pre-processing, data visualization, and data analysis tasks. Sage Maker Studio Canvas also allows users to easily share their notebooks, recipes, and data with other users and collaborate on projects. This helps to simplify the machine learning development process, accelerate the development of machine learning models, and improve collaboration among teams. IN THIS COURSE YOU WILL LEARN : Life Cycle of a Machine Learning Project Machine Learning Fundamentals Cloud Computing for Machine Learning AWS Sage Maker Canvas (NO CODE ML)