Written by Alexander Raginsky The fear that robots will destroy jobs and leave a great mass of people languishing in unemployment is almost as old as automation itself. And yet, from the Luddites onwards, the fears have been eventually proved wrong, and the economy has ended up stronger than before. Robots threaten 15m UK jobs, says Bank of England’s
Written by Alexander Raginsky Deep learning and neural networks are increasingly important concepts in computer science with great strides being made by large companies like Google and startups like DeepMind. By Nikhil Buduma (Musings of an MIT student). Deep learning. Neural networks. Backpropagation. Over the past year or two, I’ve heard these buzz words being tossed around a lot,
Written by Alexander Raginsky I read the question raised recently by the American Statistical Society (ASA) – As a statistician, what is your super power – and after reading the numerous answers, all of them very geeky and not a single one mentioning producing yield, ROI, or added value, I could not resist to post this question on DSC,
Written by Alexander Raginsky In this article, we discuss various strategies used to generate exponential traffic growth, while preserving traffic quality, and user loyalty. Our growth hacking engine is a combination of Raw data science: getting the right data sets, leveraging them, Playing with various tools and API’s: designing an automated machine-to-machine communication service between Hootsuite and Twitter /
Written by Alexander Raginsky Natural language processing, or NLP, is the machine handling of written and spoken human communications. Methods draw on linguistics and statistics, coupled with machine learning, to model language in the service of automation. OK, that was a dry definition. Fact is, NLP is at, or near, the core of just about every information-intensive process out
Written by Alexander Raginsky What I love about working at Google is the opportunity to harness cutting-edge machine intelligence for users’ benefit. Two recent Research Blog posts talked about how we’ve used machine learning in the form of deep neural networks to improve voice search and YouTube thumbnails. Today we can share something even wilder — Smart Reply, a
Written by Alexander Raginsky Not long ago, the term “data science” meant nothing to most people—even to those who worked with data. A likely response to the term was: “Isn’t that just statistics?” These days, data science is hot. The Harvard Business Review called data scientist the “Sexiest Job of the 21st Century.” So what changed? Why did data
Written by Alexander Raginsky The goal of this post is to introduce you to machine learning – and specifically Amazon Machine Learning – and help you understand how the cloud can greatly simplify the implementation of a complex machine learning algorithm. What is Machine Learning? We humans learn a lot from everything going on around us. Over time, these
Written by Alexander Raginsky If you’re fortunate enough to have a quantitative PhD, you may have thought about applying for an opening in data science. After all, it’s an exciting and well paid field and a lot of fun too. Drew Harry recently wrote on this topic. As a PhD himself he should know. Here are a few of
Written by Alexander Raginsky Google has acquired around 184 companies as of October 2015, with its largest acquisition being the purchase of Motorola Mobility, a mobile device manufacturing company, for $12.5 billion. Not all the acquisition figures are available but aggregating all the public known amounts, Google has spent atleast 28 billion USD on acquisitions. With the recent re-structuring,
