Can a machine distinguish between a honey bee and a bumble bee? Being able to identify bee species from images, while challenging, would allow researchers to more quickly and effectively collect field data. In this project, you will build a simple deep learning model that can automatically detect honey bees and bumble bees, then load a pre-trained model for evaluation. You will use keras, scikit-learn, scikit-image, and numpy, among other popular Python libraries.
This project is the third part of a series of projects that walk through working with image data, building classifiers using traditional techniques, and leveraging the power of deep learning for computer vision.
The recommended prerequisites for this project are Advanced Deep Learning with Keras in Python, Introduction to Data Visualization with Python, Naïve Bees: Image Loading and Processing, and Naïve Bees: Predict Species from Images.
Data Scientist at DrivenData
Emily Miller is a Data Scientist at DrivenData. Her personal passion is to combine data science with satellite imagery, text data, and other non-traditional data sources to make poverty alleviation efforts more effective. She was previously a Data Scientist at the Bill & Melinda Gates Foundation and a Data Science Fellow at Metis.See More