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https://github.com/computingvictor/deeplearning_practices

Evaluation Practices done for the Deep Learning subject
https://github.com/computingvictor/deeplearning_practices

cifar10 cifar100 cunef data-science deep-learning jupyter neural-network

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Evaluation Practices done for the Deep Learning subject

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# Deep Learning Practices

## About the project

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.

## Built with

- Python 3.10
- Jupyter Notebook
- Visual Code
- Tensorflow
- Sklearn
- Keras

## Content of the repository

- `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...

## Contact

Víctor Viloria Vázquez -

Project Link:

LinkedIn -

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