We came across the idea of identifying dog breeds when we realize that many of our friends were unable to find the breed of a dog whenever they saw one on the streets. We came to the realization that the use of machine learning and neural networks can be a viable solution to this issue.

What it does

DoggoBot is a Telebot incorporated with a TL-CNN model that identifies a dog's breed based on a photo of it. By submitting a photo of a dog, DoggoBot will process the photo and classify the dog's breed by running through the saved model and predicting its classification.

How we built it

We made use of mainly Tensorflow for the neural network building and TelegramBot for the TeleBot.

Challenges we ran into

Reading docs, debugging, using unfamiliar libraries and formats

Accomplishments that we're proud of

That we managed to make a product that actually runs and a model that has a fairly high accuracy and (and potential for higher given more time)

What we learned

TensorFlow, transfer learning, CNN, telegram bots, webhooks, heroku, git

What's next for DoggoBot

More accurate machine predictions!

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