With the recent machine learning boom, more and more algorithms have become available that perform exceptionally well on a number of tasks. But knowing beforehand which algorithm will perform best on your specific problem is often not possible. If you had infinite time at your disposal, you could just go through all of them and try them out. The following post shows you a better way to do this, step by step, by relying on known techniques from model selection and hyper-parameter tuning.
Saturday, February 25, 2017
Sunday, February 19, 2017
In the latest issue of this monthly digest series you can learn what happened at CES 2017, what's new in the world of self-driving cars, and how Intel got all these drones up in the sky during the Super Bowl's Halftime Show.
Monday, February 6, 2017
In the latest edition of this monthly digest series you can learn how dopamine cells influence our perception of time, why researchers are growing brains on a chip, whether split-brain patients have a split consciousness, and much more.
Saturday, January 21, 2017
Once a year, researchers meet at the University of Washington (UW) in Seattle as part of the Neural Computation and Engineering Connection to discuss what's new in neuroengineering and computational neuroscience. Organized by the UW Institute for Neuroengineering, this year's topics ranged from brain-computer interfaces to rehabilitative robotics and deep learning, with plenary speakers such as Marcia O'Malley (Rice), Maria Geffen (University of Pennsylvania), and Michael Berry (Princeton).
Sunday, January 8, 2017
Noawadays scientists find themselves spending more and more time building software to support their research. Although time spent programming is often perceived first and foremost as time spent not doing research, most scientists have never been taught how to efficiently write software that is both correct and reusable. That's why the guys behind Software Carpentry have come up with a list of best practices to help you improve your scientific code. Because after all, to quote Ralph Johnson, before software can be reusable, it has first to be usable.