Data Scientists are wild creatures who feed on data. Data Scientists are happy when there is plenty of data but they also suffer in a lot of occasions, mostly during
Data Scientists are wild creatures who feed on data. Data Scientists are happy when there is plenty of data but they also suffer in a lot of occasions, mostly during the periods of data drought. In Darwinian terms, they compete for limited resources. Therefore, those Data Scientists that develop the best adaption strategies will survive (they will have good models) and those who don’t adapt in time will perish.
For a long time, Data Scientists comunis had been able to face this situation through data hunt and/or collection, but other also use cultivation and generation techniques of new data, providing stability to their models or balancing the classes. However, a whole new world of possibilities opens when new images enter in the menus of Data Scientists.
Together with Fernando Velasco, Data Scientist at Stratio, and Raúl de la Fuente, Presales at Stratio, we will study some ways to do this, using both classical techniques and Deep Learning. Will it be useful if we take the derivative of an image?
If you want to learn more about Deep Learning and Data Augmentation, take a look at the Meetup slides and video:
Day & time
(Thursday) 7:00 pm - 9:00 pm
Calle de Manzanares, 1