Space Science with Python - AI 1-8: A Dense Neural Network
Hey Python coders,

today I would like to show you a new tutorial  video within my Space Science with Python series. I am still working on a  Machine Learning project, and this time we will use TensorFlow / Keras  to create a multi-class classifier for our asteroids reflectance  spectra.

Since our spectra data are already perfectly cleaned and  processed, even a simple Dense layer architecture provides fair  results; you'll see! And for starters, Dense-layer-based networks are  easy to "digest".

The next video will consider convolution  networks and afterwards you will see some nice Autoencoder architecture  and unsupervised classification methods. Hopefully you'll like it!

Anyway.  A word of "warning". When I create my tutorials I prepare my code, test  it, format it, test it again etc. Also this time. But: I had some  functions in the Google Colab cache. My "new" functions were not called  correctly and I figured it out in the last minutes! Anyway, I left it in  the video for others to learn from my mistake I made there. Please  note: reset your runtime when you start something new and be aware of  issues when using Notebooks in a productive environment.

GitHub: [https://github.com/ThomasAlbin/Astroniz-YT-Tutorials/blob/main/%5BML1%5D-Asteroid-Spectra/8\_dl\_dense\_multiclass.ipynb](https://github.com/ThomasAlbin/Astroniz-YT-Tutorials/blob/main/%5BML1%5D-Asteroid-Spectra/8_dl_dense_multiclass.ipynb)

YouTube: [https://youtu.be/O0rQswBZJ7o](https://youtu.be/O0rQswBZJ7o)

Cheers,  
Thomas