I have had theoretical and practical experience with a diverse array of machine learning methods: random forests and boosting, support vector machines, as well as convolutional and recurrent neural networks. I have had hands-on experience in applying and tuning these methods for real-world datasets (which often involved data cleaning) using efficient libraries in Python and R, as well as in coding some of the algorithms from the ground up. Recently, I have been fascinated to learn more about computer vision, and the machine learning that drives it. I have also been gaining exposure to the highly efficient machine learning implementations in the TensorFlow library.
Tim Wolff-Piggott
Data science and machine learning enthusiast