Multi-Label Classification of Satellite Photos of the Amazon Rainforest
Last Updated on August 24, 2020
The Planet dataset has become a standard computer vision benchmark that involves multi-label classification or tagging the contents satellite photos of Amazon tropical rainforest.
The dataset was the basis of a data science competition on the Kaggle website and was effectively solved. Nevertheless, it can be used as the basis for learning and practicing how to develop, evaluate, and use convolutional deep learning neural networks for image classification from scratch.
This includes how to develop a robust test harness for estimating the performance of the model, how to explore improvements to the model, and how to save the model and later load it to make predictions on new data.
In this tutorial, you will discover how to develop a convolutional neural network to classify satellite photos of the Amazon tropical rainforest.
After completing this tutorial, you will know:
- How to load and prepare satellite photos of the Amazon tropical rainforest for modeling.
- How to develop a convolutional neural network for photo classification from scratch and improve model performance.
- How to develop a final model and use it to make ad hoc predictions on new data.
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