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400 Birds Species Classification

🎦 Demo 👇

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:-

📝 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.

📁 Libraries Used

🖍️ scikit-learn 🖍️ Keras 🖍️ Tensorflow 🖍️ matplotlib 🖍️ seaborn 🖍️ numpy 🖍️ pandas 🖍️ prettytable 🖍️ Flask

🛠️ 🧰 Tools and Softwares Used

  • Google Colab
  • Jupyter Notebook
  • Sublime Text

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Classification of 400 birds species using Deep Learning

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