Upsides of this new AWS service: * great UI and visualisations. * solid choice of metric to evaluate the results. Maybe things moved on since I was working on it, but the use of AUC, false positives and false negatives was pretty new when I was working on it. (er, 10 years ago!) Downsides: * it could do with more support for unsupervised learning algorithms. Supervised learning means you need to provide training data, which in itself can be hard work. My experience with logistic regression in the past is that it requires very accurate training data, too — its tolerance for misclassified training examples is poor. * Also, in my experience, 80% of the hard work of using ML algorithms is writing good tokenisation and feature extraction algorithms. I don’t see any help for that here unfortunately. (probably not that surprising as it requires really detailed knowledge of the input data to know what classes can be abbreviated into a single class, etc.)
these are great. I’ve run into rule #3 (“fancy algorithms are slow when n is small, and n is usually small”) several times…
Any message posted to an SNS topic can trigger the execution of custom code you have written, but you don’t have to maintain any infrastructure to keep that code available to listen for those events and you don’t have to pay for any infrastructure when the code is not being run. This is, in my opinion, the first time that Amazon can truly say that AWS Lambda is event-driven, as we now have a central, independent, event management system (SNS) where any authorized entity can trigger the event (post a message to a topic) and any authorized AWS Lambda function can listen for the event, and neither has to know about the other.
Texting while behind the wheel has overtaken drink driving as the biggest cause of death among teenagers in America. More than 3,000 teenagers are killed every year in car crashes caused by texting while driving compared to 2,700 from drink driving. The study by Cohen Children’s Medical Center also discovered that 50 per cent of students admit to texting while driving.
Conducting such a widespread attack clearly demonstrates the weaponization of the Chinese Internet to co-opt arbitrary computers across the web and outside of China to achieve China’s policy ends. The repurposing of the devices of unwitting users in foreign jurisdictions for covert attacks in the interests of one country’s national priorities is a dangerous precedent — contrary to international norms and in violation of widespread domestic laws prohibiting the unauthorized use of computing and networked systems.
How to build an Intelligent Personal Assistant: ‘Sirius is an open end-to-end standalone speech and vision based intelligent personal assistant (IPA) similar to Apple’s Siri, Google’s Google Now, Microsoft’s Cortana, and Amazon’s Echo. Sirius implements the core functionalities of an IPA including speech recognition, image matching, natural language processing and a question-and-answer system. Sirius is developed by Clarity Lab at the University of Michigan. Sirius is published at the International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS) 2015.’
If you’re not immersed in the naming business you may find the jargon in it hard to understand. The basic upshot is this: the IPC believes that the mechanisms that were enacted to protect trademark holders during the deluge of new TLD rollouts are being gamed by the .SUCKS TLD operator to extort inflated fees from trademark holders.(via Nelson)
Links for 2015-04-13
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