Data science and Machine learning

I use deep learning models to analyze biometric data to use in image recognition and vocal recognition. I use R and Python to process and analyze large sets of data. These are some small toy projects:

Cleaning Spotted-wing drosophila and weather station data

The script I used to clean and process a large database of trap and weather station data can be accessed here:

https://rendonda.github.io/rendonda/swd_weather_cleanup.html

Automated recognition of insect pests in traps using neural networks

For this project, we are fine-tuning a pretrained faster_rcnn model to accurately identify males and females of the spotted-wing drosophila (Drosophila suzukii) and individuals of Drosophila melanogaster in mixed images.

https://biodatarium.github.io/SWD_image_recognition/index.html

Pest abundance analytics using machine learning

We use machine learning models to determine if we can predict the risk for pest infestation in a particular site based on environmental variables.

A case study for a single area and sample script for this project can be found at:
https://rendonda.github.io/swd_trap_counts/

Birsong recognition using 1D Convnet neural networks

https://biodatarium.github.io/birdcall/