Summary: At least one instance of Real Time Predictive Model development in a streaming data problem has been shown to be more accurate than its batch counterpart. Whether this can be generalized is still an open question. It does challenge the assumption that Time-to-Insight can never be real time. A few months back I was making my way through the latest literature on "real time analytics" and "in stream analytics" and my blood pressure was rising. The cause was the developer-driven hyperbole that claimed that the creation of brand new insights using advanced analytics has become "real time".

The generate method takes in a conditional frequency distribution. Think – how many times did each word appear after'farm'? That is what a conditional frequency distribution outputs (for all words, not just'farm'). The rest of the generate function does is output text based on the distribution observed in the training data. I did this by making an array with each word that appeared after the current word.

Nasa has announced that it has found evidence of flowing water on Mars. Scientists have long speculated that Recurring Slope Lineae -- or dark patches -- on Mars were made up of briny water but the new findings prove that those patches are caused by liquid water, which it has established by finding hydrated salts. Several hundred camped outside the London store in Covent Garden. The 6s will have new features like a vastly improved camera and a pressure-sensitive "3D Touch" display

New York – When Toyota aired a Super Bowl television ad featuring a surprisingly quick Prius gas-electric hybrid eluding police, it marked a turning point for the auto industry. For years, automakers pushed fuel efficiency to sell hybrid and electric vehicles. Now, in an era of cheap gasoline, the message is: These cars are faster and quieter than their gas-powered counterparts. And, yes, you still save on fuel. "They've graduated out of the class of something that's a bit of an oddity to drive," says Mike O'Brien, vice president of product planning for Hyundai.

Pennsylvania is set to consider a ban on drones in the skies above all 1.5 million acres of state game lands following several incidents of harassment of wildlife by the unmanned aerial vehicles.

UPDATE: Mar 20, 2016 - Added my new follow-up course on Deep Learning, which covers ways to speed up and improve vanilla backpropagation: momentum and Nesterov momentum, adaptive learning rate algorithms like AdaGrad and RMSProp, utilizing the GPU on AWS EC2, and stochastic batch gradient descent. We look at TensorFlow and Theano starting from the basics - variables, functions, expressions, and simple optimizations - from there, building a neural network seems simple! Deep learning is all the rage these days. What exactly is deep learning? Well, it all boils down to neural networks.

If you think deep, you'd realize the whole process of predictive modeling is a war. Consider the data set as your opponent. Your win will depend on the intuitive usage of your knowledge & strategy to get highest accuracy. So, how many times have you won this battle? I realized it last week.

Twitter started the trend of'People to Follow'. This later got replicated by other platforms such as Facebook, Linkedin, Quora and GitHub. This cool feature lets you connect with the rockstars of various domains and get an access to what is going on their end without bothering them much. For the influencers, this has become an effective way to communicate with their followers. The lives of people on GitHub doesn't appear to as tempting as you would observe on other platforms, but if you love coding, programming and data science, you'll surely enjoy the company of 9 million users on this platform!

Over a year ago, following an original presentation at MLConf, I wrote a blog post entitled "10 Lessons Learned from building ML systems". At that point, I was leading the Algorithms Engineering team at Netflix and those lessons reflected lessons we had learned there over the last few years. When you do a post/presentation like that, you don't really know how it is going to be received. Some things might be obvious to many while others might be controversial and some will not agree. It turns out though that it was very well received and referenced elsewhere (e.g.

The veteran provider of document capture and OCR software has a new product suite aimed at enabling business applications to read and understand natural language, and thus help their users make better-informed decisions. Is the time right for a resurgence of interest in text analytics?