This repository will include the evaluable practices of the subject 'Deep Learning' belonging to the Master in Data Science at CUNEF during the academic year 2022-2023.
- Python 3.10
- Jupyter Notebook
- Visual Code
- Tensorflow
- Sklearn
- Keras
Practice 1- Cifar 100:
In this practice we will perform different tests of neural networks. Once 8 neural networks of different characteristics have been modeled, we will keep the one that has achieved the best result in the validation set.
Subsequently, we will study how the score affects the variation of the batch size and the number of neurons in each layer, plotting the results.
Finally, we will make a comparison between different Machine Learning models and the resulting scores of each one.
Practice 2- Best Score:
In this practice we will have to obtain the highest score with the CIFAR-100 dataset. For this we will have to use the different types of networks/layers and optimizers seen in class, modifying their hyperparameters, batch sizes, etc...
Víctor Viloria Vázquez - victor.viloria@cunef.edu
Project Link: https://github.com/ComputingVictor/DeepLearning_Practices
LinkedIn - https://www.linkedin.com/in/vicviloria/