Dog-Breed Classifier

Project Overview

Welcome to the Convolutional Neural Networks (CNN) project! In this project, you will learn how to build a pipeline to process real-world, user-supplied images. Given an image of a dog, your algorithm will identify an estimate of the canine’s breed. If supplied an image of a human face, the code will identify the resembling dog breed.

Along with exploring state-of-the-art CNN models for classification, you will make important design decisions about the user experience for your app. By completing this lab, you demonstrate your understanding of the challenges involved in piecing together a series of models designed to perform various tasks in a data processing pipeline.

Each model has its strengths and weaknesses, and engineering a real-world application often involves solving many problems without a perfect answer.
Your imperfect solution will nonetheless create a fun user experience!

Project Instructions

Clone the project from the GitHub repository or complete the code in your in-classroom workspace (detailed submission instructions, below). Follow the instructions in the notebook to complete the project.

Evaluation

Your project will be reviewed by a Udacity reviewer against the CNN project rubric. Review this rubric thoroughly, and self-evaluate your project before submission. All criteria found in the rubric must meet specifications for you to pass.

Project Submission

When you are ready to submit your project, collect the following files and compress them into a single archive for upload:

  • The dog_app.ipynb file with fully functional code, all code cells executed and displaying output, and all questions answered.
  • An HTML or PDF export of the project notebook with the name report.html or report.pdf.
  • Any additional images used for the project that were not supplied to you for the project. Please do not include the project data sets in the dogImages/ or lfw/ folders. These files will make your project too large to submit.

Alternatively, your submission could consist of the GitHub link to your repository.

Submitting Using the Workspace

If you used the provided workspace to complete the project, the easiest way to submit would be the following:

  1. Create an an HTML version of the dog_app notebook by running the code in the Create Submission Files workspace
  2. In that workspace, continue executing cells to zip your files into a dog-project folder.
  3. Navigate back to the home directory by clicking the orange Jupyter icon.
  4. Download that zip version of the notebook to your computer using 'File: Download as…' This will be the zip file you submit on this page!

Project Submission Checklist

Before submitting your project, please review and confirm the following items.
I am confident all rubric items have been met and my project will pass as submitted.
Project builds correctly without errors and runs.
All required functionality exists and my project behaves as expected per the project's specifications.

Once you have checked all these items, you are ready to submit!

Ready to submit your project?

Click on the "Submit Project" button and follow the instructions to submit!