Mobile Testing, Semantic Segmentation, Salary Gossip, and Word Analogies
- OWASP Mobile Testing Guide — a work in progress, but useful.
- Semantic Segmentation Using Deep Learning — review of the techniques that help you categorize pixels in an image by which object in the image they belong to.
- Salary Gossip — Top 6% or so of engineers at Amazon, Oracle, Google, Facebook, Twitter are paid more than $1.3 million per year. Next 11% make $650,000 on average. […] $600,000 to $2 million packages are similarly becoming common in the U.S. Software engineers with 10 years experience should be making ~$420,000 per year with ~$210,000 salary. […] $240,000 to $470,000 packages are now common in China. […] Fresh MS graduates in the U.S. are getting $220,000+ packages at Google, Amazon, eBay, Twitter, LinkedIn, Airbnb, Facebook, Snapchat, will add more. No idea of the source, so take it all with a pillar of salt, but … holy crap. As a Kiwi, I approve of Do not go to Singapore, Germany, or U.K. Go to Canada, Australia, France, New Zealand, or South Africa instead.
- Word Vectors and SAT Analogies — clever approach using the SAT analogy questions to test how well the word vector technique (“king – man + woman = queen”) holds up to relatively real-life situations. He got 49% accuracy but notes: These methods are not the best-performing non-human technique for these SAT analogy questions. Littman and Turney report several. Latent Relational Analysis comes in at 56% accuracy, against the average U.S. college applicant at 57%.
Continue reading Four short links: 6 July 2017.