LULC Satellite Image Classification Using Deep Learning: How to Train a Deep Learning Model in Colab

In this video, we will learn together how to train a deep learning model for land use land cover classification using Sentinel-2 satellite data.
The code examples are available on our GitHub page:
github.com/BEEILAB/LULC-Class...
The EuroSat dataset can be found in the following link:
github.com/phelber/eurosat#
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[@vloghung118]

Your positive energy always shines through in your videos. Keep up the amazing work!

[@BEEiLabTV]

Thank you so much!

[@user-ei7rn2wh6u]

Your channel is truly a treasure trove of amazing content. Keep up the great work!

[@BEEiLabTV]

Glad you enjoy it!

[@TomBiensia]

Your videos are always a joy to watch. Thanks for the great content!

[@BEEiLabTV]

Glad you like them!

[@amjedmehmood5654]

The information in this video is so helpful. Thank you for sharing!

[@BEEiLabTV]

Glad it was helpful!

[@Nightmare.826]

Your videos are always so unique and creative. Keep up the great work!

[@BEEiLabTV]

Thank you so much!

[@AlexAnticona94]

Felicidades por su video y muchas gracias por la enseñanza, saludos desde Perú

[@peruvian12]

I love the way you explain things in your videos. So clear and easy to understand!

[@BEEiLabTV]

Glad you like them!

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🎉🎉🎉

[@saleemullahbaig9925]

I am a little confused here as to why you use binary cross entropy as the loss function because you are working on a multi-class classification dataset.

[@BEEiLabTV]

Yes, you are right. Here, we have two options. First, we can use sigmoid acrivation function with binary cross entropy and secondly, we can use softmax with categorical cross entropy.

[@saleemullahbaig9925]

​@@BEEiLabTV oh. i got it and thanks for your response.