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Deep Learningintermediate

Elephant Species Classification using Deep Learning and Transfer Learning

This project focuses on developing an automated elephant species classification system using deep learning techniques, specifically convolutional neural networks (CNNs) and transfer learning. By accurately identifying elephants from photographic data, the system aims to enhance wildlife conservation efforts through improved monitoring and data analysis.

16 lectures

What You Will Learn

Mastering the fundamentals of image classification using deep learning
Implementing transfer learning techniques for efficient model training
Building CNN models using TensorFlow or Keras
Applying pre-trained models like MobileNetV2 and Xception for image classification
Developing a Streamlit application for real-time species identification
Deploying machine learning models on AWS EC2
Understanding different image augmentations and optimization methods for model performance

System Architecture

Elephant Species Classification using Deep Learning and Transfer Learning Architecture Diagram

High-level architecture overview of the Elephant Species Classification using Deep Learning and Transfer Learning .

What You'll Build

  • A base image classification model using a CNN architecture
  • Transfer learning models using MobileNetV2 and Xception
  • A Streamlit application for real-time wildlife species identification
  • A deployed species identification service on AWS EC2
Elephant Species Classification using Deep Learning and Transfer Learning
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