README.md

Image classification by CIFAR 10

This project makes image classification using convolutional networks.

See the jupyter notebook

Motivation

Understand convolutional networks.

Built With

• Python 3 - Language
• Anaconda - Python Data Science Platform
• Jupyter notebook - Web application that allows to create documents that contain live code

Dataset

CIFAR 10 dataset.

Getting Started

Prerequisites

1. Download and install Anaconda
2. Update Anaconda

$ conda upgrade conda 
$ conda upgrade --all 

Install

1. Clone and enter into the project's root directory by command line

$ git clone https://github.com/machine-learning-experiments/image-classification-by-cifar-10.git

2. Create and activate enviroment

$ conda env create -f enviroment.yaml 
$ conda activate image-classification-by-cifar-10 

or

conda create --name image-classification-by-cifar-10 python=3
source activate image-classification-by-cifar-10
conda install numpy jupyter notebook tqdm tensorflow matplotlib scikit-learn

3. Start jupyter notebook

$ jupyter notebook 

4. Your browser will open showing a list of files, click on the dlnd_image_classification.ipynb notebook file

Author

Lorival Smolski Chapuis

This project was developed during the deep-learning nanodegree from Udacity