{"id":10986,"date":"2019-09-06T09:00:43","date_gmt":"2019-09-06T13:00:43","guid":{"rendered":"https:\/\/blogs.mathworks.com\/pick\/?p=10986"},"modified":"2019-09-05T20:05:37","modified_gmt":"2019-09-06T00:05:37","slug":"winner-of-machine-learning-hackathon","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/pick\/2019\/09\/06\/winner-of-machine-learning-hackathon\/","title":{"rendered":"Winner of Machine Learning Hackathon"},"content":{"rendered":"\r\n

Jiro<\/a>‘s Pick this week is Deep Learning Hackathon with Transfer Learning<\/a> by Paola Jaramillo<\/a>.<\/p>

Deep learning is becoming more accessible to casual programmers, especially with many pretrained deep neural networks<\/a> that people can download from the Add-On Explorer<\/a>. These pretrained networks are trained on some specific set of images, and they can be a great starting point for new tasks. Adapting a pretrained network for a new task is called transfer learning<\/a>.<\/p>

This entry by Paola is an example of transfer learning that won her first place<\/b> at a Hackathon on Deep Learning for Agriculture<\/a> by Itility. The challenge was to classify the species of plants from the images.<\/p>

\r\n<\/img>\r\n<\/p>

She wrote about it in the Deep Learning Blog<\/a>, so I’ll let you read the details there.<\/p>

Comments<\/b><\/p>

Let us know what you think here<\/a> or leave a comment<\/a> for Paola.<\/p>