Part 0: Working through the Kaggle aerial cactus image classification challenge

In this four part series, we will be working through the Kaggle Aerial Cactus Identification challenge from 2019. The series will cover the following topics:

• Part 1: Pre-processing and dimensionality reduction with autoencoders
• Part 2: Comparing dimensionality reduction between autoencoders and principle component analysis (PCA)
• Part 3: Model selection and implementation with convolutional neural networks (CNN)
• Part 4: Model interpretation with LIME and concluding remarks

The aim of this series is to show an example implementation of the full data science pipeline for an image classification problem.

All the code for this series is available in this GitHub repository.