August 14, 2013Posted by on
I been reading and wishing I could start using “Deep Learning” to classify network traffic. There’s been a lot of talk over deep learning in the last year in the ML community. I recently watched Peter Norvig on the latest updates and how Google in using deep neural networks and how they are beating conventional algorithms in their voice, video and image classification applications.
I’m excited to hear that malware detection, speech recognition, computer vision, and molecular activity prediction are all early adopters. I’m excited to start see network security vendors join the gaggle. The idea of neural networks is hardly new but today’s neural networks can efficiently process many more neurons, with many more layers, than before. Thanks to improvements in CPU and GPU technologies.
Geoff Hinton introduced a new algorithm which allows for efficiently training larger and deeper neural networks than in the past.
I’m hoping that NN will provide an upper hand for InfoSec.
August 10, 2013Posted by on
July 31, 2013Posted by on
July 29, 2013Posted by on
User experience (UX) involves a person’s emotions about using a particular product, system or service. User experience highlights the experiential, affective, meaningful and valuable aspects of human-computer interaction and product ownership. Additionally, it includes a person’s perceptions of the practical aspects such as utility, ease of use and efficiency of the system. User experience is subjective in nature because it is about individual perception and thought with respect to the system. User experience is dynamic as it is constantly modified over time due to changing circumstances and new innovations.
July 11, 2013Posted by on
Prescriptive analytics is the third phase of business analytics, a decision-modelling system for industry. The first stage is descriptive analytics, which looks at past issues and describes them; it tells you what happened and why after the fact. The second stage is predictive analytics, which combines historical data with predictive algorithms to guess the probability of future events; it tells you what will happen. But prescriptive analytics claims to go even further. It applies a multitude of business rule algorithms, multiple mathematical and computational modeling systems to automatically synthesize hybrid data sets and answer not only what will happen but what also needs to be done about it. Put another way, prescriptive analytics continuously and automatically tries to anticipates the what, when, and why of unknown future events. And it has the potential to be scary accurate.
July 9, 2013Posted by on
June 28, 2013Posted by on
June 27, 2013Posted by on
Persuasive technology is broadly defined as technology that is designed to change attitudes or behaviors of the users through persuasion and social influence, but not through coercion (Fogg 2002). Such technologies are regularly used in sales, diplomacy, politics, religion, military training, public health, andmanagement, and may potentially be used in any area of human-human or human-computer interaction. Most self-identified persuasive technology research focuses on interactive, computational technologies, including desktop computers, Internet services, video games, and mobile devices (Oinas-Kukkonen et al. 2008), but this incorporates and builds on the results, theories, and methods of experimental psychology, rhetoric (Bogost 2007), and human-computer interaction. The design of persuasive technologies can be seen as a particular case of design with intent (Lockton et al. 2010).
June 26, 2013Posted by on
June 25, 2013Posted by on