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Classification of 400 birds species using Deep Learning

Python 0.01% HTML 0.01% Jupyter Notebook 99.98%

400-birds-species-classification's Introduction

400 Birds Species Classification

๐ŸŽฆ Demo ๐Ÿ‘‡

Demo

Self-written Medium blog: 400 Birds Species Classification

Aim of this Project

  • This project aims to predict revenue for a set of customers for a time period in the future.
  • Different machine learning & deep learning techniques were used.
  • Deployment was done using Flask API on an AWS EC2 instance.

Datasets:-

  • Source โžก๏ธ Kaggle

๐Ÿ“ Best Model

  • VGG19 with fne tuning of last few layers by freezing first 17 layers resulted in lowest loss of 0.14 on completely unseen test images.

Deployment using Flask API

  • A simple web-app has been built using this model (as shown in the Demo).
  • This web-app has also been Deployed using Flask API.
  • Using this web-app, you can upload an image of a bird and the web-app will return the species name in the UI.

๐Ÿ“ Libraries Used

๐Ÿ–๏ธ scikit-learn ๐Ÿ–๏ธ Keras ๐Ÿ–๏ธ Tensorflow ๐Ÿ–๏ธ matplotlib ๐Ÿ–๏ธ seaborn ๐Ÿ–๏ธ numpy ๐Ÿ–๏ธ pandas ๐Ÿ–๏ธ prettytable ๐Ÿ–๏ธ Flask

๐Ÿ› ๏ธ ๐Ÿงฐ Tools and Softwares Used

  • Google Colab
  • Jupyter Notebook
  • Sublime Text

400-birds-species-classification's People

Contributors

toushalipal6991 avatar

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