Sebastian Lague | Neural Networks | E03: data and evaluation (unfinished series) @SebastianLague | Uploaded 6 years ago | Updated 4 days ago
In this episode we load our training data and evaluate how accurate the network is with random weights.
Download the data here (see readme for more info on loading):
https://github.com/SebLague/Mnist-data-numpy-format
Code:
https://github.com/SebLague/Neural-Network-python
I owe a lot to this excellent online book on neural networks:
http://neuralnetworksanddeeplearning.com/
Support the creation of more tutorials:
https://www.patreon.com/SebastianLague
In this episode we load our training data and evaluate how accurate the network is with random weights.
Download the data here (see readme for more info on loading):
https://github.com/SebLague/Mnist-data-numpy-format
Code:
https://github.com/SebLague/Neural-Network-python
I owe a lot to this excellent online book on neural networks:
http://neuralnetworksanddeeplearning.com/
Support the creation of more tutorials:
https://www.patreon.com/SebastianLague
![[Unity] Procedural Planets (E05: shader)](https://i.ytimg.com/vi/itnLOlQ2QFo/hqdefault.jpg "[Unity] Procedural Planets (E05: shader)
In this episode we use shadergraph to create a simple shader for our planet.
Get the project files for this episode:
http://github.com/SebLague/Procedural-Planets
Support the creation of more tutorials and get early access to new videos: https://www.patreon.com/SebastianLague")
