Arcgis api for python geospatial deep learning with arcgis learn

arcgis api for python is a powerful library that allows you to work with geospatial data and perform various spatial analysis tasks. with arcgis learn, you can leverage deep learning techniques to extract valuable information from geospatial data. in this tutorial, we will guide you through the process of using arcgis learn for geospatial deep learning.

below are the steps to get started with geospatial deep learning using arcgis learn:

1. install arcgis api for python:
make sure you have arcgis api for python installed. you can install it using the following command:


2. import necessary modules:


3. prepare the data:
use the `prepare_data` function to prepare your geospatial data for deep learning tasks. this function allows you to load, preprocess, and split your data into training and validation sets.


4. instantiate the deep learning model:
create an instance of the deep learning model you want to use for your geospatial analysis task. in this example, we will use `deeplabv3` for semantic segmentation.


5. train the model:
train the deep learning model using the prepared data. you can specify the number of epochs and other training parameters.


6. perform inference:
once the model is trained, you can perform inference on new geospatial data to extract information. use the `predict` method to generate predictions.


7. visualize the results:
visualize the predictions on a map or export them as a geospatial dataset for further analysis.


by following these steps, you can utilize arcgis learn for geospatial deep learning tasks. experiment with different deep learning models and tuning parameters to achieve the best results for your specific geospatial analysis needs.

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