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An end-to-end example of a serverless machine learning pipeline for multiclass classification on AWS with SageMaker Pipelines, Data Wrangler, Athena and XGBoost.
The Practical Data Science Specialization brings together these disciplines using purpose-built ML tools in the AWS cloud. It helps you develop the practical skills to effectively deploy your data science projects and overcome challenges at each step of the ML workflow using Amazon SageMaker. This Specialization is designed for data-focused develop
This project aims to answer some questions about weather data from csv files, using Python and Data Engineering
These are the handwritten notes on Coursera's Practical data science specialization course.