So I'm buliding a small list of many different ML libraries, but don't want to miss out too many (sure I will do some). Anything else which you are using and think needs attention please feel free post.

"Intelligent system designers do have ethical responsibilities." I have interviewed John Markoff, technology writer at The New York Times. In 2013 he was awarded a Pulitzer Prize. The interview is related to his recent book "Machines of Loving Grace: The Quest for Common Ground Between Humans and Robots, published in August of 2015 by HarperCollins Ecco. Do you share the concerns of prominent technology leaders such as Tesla's chief executive, Elon Musk, who suggested we might need to regulate the development of artificial intelligence?

Imagine you took a world-class business writer and asked him to rate the quality of several pieces of content in a blind test. Would he be able to tell which ones were created by humans and which ones were produced by automated writing? Well, that's exactly what Mark Schaefer addressed recently. To find out that… "two of the top three posts were written by a computer." Given that Mark is one of the most respected speakers and writers on marketing, with a successful blog, an impressive audience and numerous publications, I wouldn't blame you if it sounded so.

In 2014, Google acquired the artificial intelligence startup DeepMind, but it wasn't cheap. With a price tag of 500M, there must have been something special that Google saw in DeepMind that was worth acquiring. While the company hasn't produced any actual products for commercial use, they have focused on machine learning. Machine learning is a type of artificial intelligence that aims to provide computers with the ability to learn new information without being directed to do so. Machine learning involves the development of computer programs that have the ability to teach themselves to grow and alter themselves when presented with new data.

"Figuring out how to build ethical autonomous machines is one of the thorniest challenges in artificial intelligence today," researchers from the University of Toulouse and MIT's Media Lab argue in their paper in the journal Science on a survey that tries to work out how moral people want their self-driving cars to be. But is it the thorniest challenge? I'd argue the thorniest problem is working out some form of AI that is even capable of making ethical decisions. Self-driving algorithms have some way to go before we can even begin to consider whether they can weigh up the ethics of a situation along similar lines to Isaac Asimov's famous three laws. And you then have the knotty problem of determining what is truly ethical.

Here are some helpful R functions for regression analysis grouped by their goal. The name of package is in parentheses. Base has a method for objects inheriting from class "lm" (stasts) This is a generic function, but currently only has a methods for objects inheriting from classes "lm" and "glm" (stasts) AIC: Generic function calculating the Akaike information criterion for one or several fitted model objects for which a log-likelihood value can be obtained, according to the formula -2*log-likelihood k*npar, where npar represents the number of parameters in the fitted model, and k 2 for the usual AIC, or k log(n) (n the number of observations) for the so-called BIC or SBC (Schwarz's Bayesian criterion) (stats) Four plots (selectable by which) are currently provided: a plot of residuals against fitted values, a Scale-Location plot of sqrt{ residuals } against fitted values, a Normal Q-Q plot, and a plot of Cook's distances versus row labels (stats) Performs Bartlett's test of the null that the variances in each of the groups (samples) are the same (stats) bgtest: Breusch-Godfrey Test (lmtest) bptest: Breusch-Pagan Test (lmtest)

In September, San Diego robotics startup Brain Corporation will introduce artificial intelligence software that allows giant commercial floor-cleaning machines to navigate autonomously. The follow-up offering it wants to develop may be even more forward-looking: A training and certification program for janitors to operate the machines. The program, still in early stages of planning, is aimed at helping janitors maximize efficiency and establishing standards and best practices for the use of robots in janitorial work, according to Brain Corporation. The company says it is not aware any other such training program exists. There's additional incentive for Brain Corp. to offer training options.

Consider TPOT your Data Science Assistant. TPOT is a Python tool that automatically creates and optimizes machine learning pipelines using genetic programming. TPOT will automate the most tedious part of machine learning by intelligently exploring thousands of possible pipelines to find the best one for your data. Once TPOT is finished searching (or you get tired of waiting), it provides you with the Python code for the best pipeline it found so you can tinker with the pipeline from there. TPOT is built on top of scikit-learn, so all of the code it generates should look familiar... if you're familiar with scikit-learn, anyway.

In this Maker Mini, @pjdecarlo walks through an elaborate demonstration of Windows IoT Core and Azure Machine Learning that was recently unveiled at the Microsoft exhibition booth at First Robotics 2016 in St. Louis, MO. We'll check out brand new features included in the current preview release of Windows IoT Core, notably the Windows IoT Remote Client and PWM Bus Provider. Plus we will get to see an example of an Machine Learning Experiment being piped into a web-frontend for a live simulation that you can replicate for yourself @ internetofyourthings.com.

For the past two days, Samsung has been talking about its Galaxy Note 7's iris scanner on its online newsroom, highlighting the reasons why this new mobile security feature could be a big game changer in the mobile industry. Just yesterday, the South Korean-headquartered company discussed how the iris scanning technology is making Samsung Pass even more secure. Samsung Pass is part of Knox, the comprehensive security platform of Samsung's recent handsets. Pass previously centered on fingerprint recognition via the fingerprint scanner as a means of enhancing the identity verification process of the phone itself and certain apps. With the addition of the iris scanner, Samsung claims that the Note 7's security has reached the ultimate level thanks to this advanced biometric authentication that does not require IDs or passwords for identity authentication.