README.md

Deep Learning Models

This repository contains different Deep Learning models with many different datasets and different tasks.

You can train and test different Python Keras Deep Learning models for different tasks and datasets!

Models

The models are/can be trained on different datasets. For now, there are:

Image Classification

Iris: Recognize different Iris using their features - acc: 88%

Cifar10: Categorize different images (from plane to dog) by training on 60000 images - acc: 80%

Cifar100: Categorize different images on up to 100 different labels - acc: 45%

Fashion_MNist: Categorize different clothing images - acc: 94%

Time-Series Regression

Finance_MMM: Analyze MMM stock market trend - mse: 0.05

Deployment

Clone this repository:

  git clone https://github.com/gobbez/DeepLearningModels.git

Go to the folder and activate virtual environment:

  cd DeepLearningModels

Install Python modules:

  pip install -r requirements.txt

Take one model, explore its code or use it! Have fun!

Objectives

The objective is to collect as many different datasets and possible tasks in order to improve!

My local equipment

For the moment, I'm using either my pc CPU or Google Colab with TPU.

Every Deep Learning model will be done with Keras (and Tensorflow backend).

Updates

08/04/2025: Revisited every model and updated their READMEs with images and better descriptions

Conclusions

There are different, high performance models, that you can train, test and use for your needs! 💥

Documentation

Keras Python