Remove 2015 Remove Cross Validation Remove Machine Learning
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Build a crop segmentation machine learning model with Planet data and Amazon SageMaker geospatial capabilities

AWS Machine Learning Blog

In this post, we illustrate how to use a segmentation machine learning (ML) model to identify crop and non-crop regions in an image. Our results reveal that the classification from the KNN model is more accurately representative of the state of the current crop field in 2017 than the ground truth classification data from 2015.

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The Evolution of Tabular Data: From Analysis to AI

Towards AI

Tabular data has been around for decades and is one of the most common data types used in data analysis and machine learning. This exposed many data scientists and machine learning engineers to the power of analyzing and building models on tabular data. The dataset is under Apache 2.0, and it is updated daily.