I don't know about all of you, but flying doesn't always go smoothly for me. I have had some horror stories I could tell you about weird delays I have encountered while flying. Wouldn't it be nice to know how much your flight will probably be delayed and why? Well, that's what this project will attempt to do. Granted, the data scientists over at Hortonworks did a very similar project (and a well done one in my opinion!) just a few months ago. My project will be a little different from theirs in that instead of doing a classification problem (yes/no for a delayed flight), this will be a regression problem where I will try to predict the delay time in number of minutes (which can be negative). The regression model will not be restricted to a single city, so we are going to be working with a very large number of training examples! To complete this project, we need some data about flights. Fortunately, the government keeps such a resource available that we are going to examine in this project. Similar to the project about faculty salaries, this post will be split into two major parts: exploratory data analysis and feature engineering in R, with regression model implementation in Python.

UBTECH's Stormtrooper missed Force Friday and The Last Jedi's release -- no surprise, really. The robotic toy moves pretty slowly, all things told. Perhaps it was a matter of getting things just right, or maybe it was the pains of dealing with such a high-profile license for the first time. Whatever the case, the Chinese robotics startup has just taken the wraps off one last piece of Star Wars tech for the year -- and it's a doozy.

Over the last 12 months, we've seen some incredibly stirring and thoughtful conversations from our members on LinkedIn about hot topics like the opioid crisis, immigration reform, the U.S. tax bill, healthcare coverage and harassment cases. These events sparked hundreds of thousands of insightful comments from professionals on LinkedIn around the world -- and will certainly have lasting consequences for years to come. Amazon has become a kind of corporate obsession in 2017. Companies big and small are watching the retailer: A review of last quarter's earnings calls shows that Amazon's name came up almost four times as often as President Trump's, and six times as often as wages. Amazon's moves this year proved that it's corporate tentacles are expanding, from purchasing Whole Foods to searching for its HQ2, a $5 billion project that promises to bring 50,000 high-paying jobs to the winning locale.

The first animals to be domesticated by humans were wolves, although the jury is still out on when exactly this occurred. Now a menagerie of animals is considered companion animals or pets, from the fuzzy chinchilla to the majestic horse. The original reasons for domestication were as varied as the species themselves: protection, hunting, travel and companionship. Today, pets are considered by their owners to be members of the family. They have their own toys, a special place on the sofa or even their own room. According to the U.S. Bureau of Labor Statistics, Americans individually spent an average of $500 on their pets for a collective total of $66.75 billion, three times more than 20 years earlier.

Theresa May has defended the use of drone strikes against British citizens, saying the killing of Islamic State's Reyaad Khan in 2015 was "necessary and proportionate" and that she would authorise such strikes in the future. The prime minister said there had been no alternative to the killing of Khan in a precision airstrike in Syria because "a direct and imminent threat was identified by the intelligence agencies". There was "a clear legal basis for action in international law", she added. May was responding to the publication on Wednesday of a series of reports on counter-terrorism, cyber-security and other intelligence issues. The legality of drone strikes against a country's own citizens is controversial both in the UK and the US.

A set of decades-old algorithms has finally met with adequate data and computing power. Organizations around the world are using this artificial intelligence to make better decisions; government agencies are not far behind either. AI has shown with tremendous potential and unbelievable promise. It is but natural that AI be applied to automate workflows based on something each citizen uses everyday -- language. Majors companies like IBM, Amazon and Microsoft, as well as upstarts like ours, Coseer, are investing in AI for language. The obvious course is to start with algorithms that have been so successful elsewhere.

Whether we're aware of them or not, algorithms affect a huge part of our lives. Now, in a US-first, New York is taking steps to address potential algorithmic biases in services provided by municipal agencies. City council has passed a bill that would -- if signed by Mayor de Blasio -- create a task force to examine if and how service algorithms are biased, how citizens can appeal decisions made by algorithms if they feel they're unfair, and if agency source code could be made publicly available. "Automated decision systems" are responsible for determining outcomes on a wide range of city/citizen matters. Take eligibility for bail, for example.

While EMMA is a relatively simple application, developers are thinking bigger as well: Today's cognitive technologies can track the course, speed, and destination of nearly 2,000 airliners at a time, allowing them to fly safely.4 Over time, AI will spawn massive changes in the public sector, transforming how government employees get work done. It's likely to eliminate some jobs, lead to the redesign of countless others, and create entirely new professions.5 In the near term, our analysis suggests, large government job losses are unlikely. But cognitive technologies will change the nature of many jobs--both what gets done and how workers go about doing it--freeing up to one quarter of many workers' time to focus on other activities.

DEC 3 marked the opening of the annual World Internet Conference in Wuzhen. The global techfest was attended by the CEOs of some of the world's largest companies, including Apple's Tim Cook and Google's Sundar Pichai, alongside Alibaba Group Holding's Jack Ma, Tencent Holdings' Pony Ma and Baidu's Robin Li, as well as the top names in artificial intelligence (AI), robotics, digital payments and cybersecurity. The opening session on the first day was aptly titled "Artificial Intelligence: Smarter World, Better Life". That a small Chinese town 90 minutes' drive from Shanghai would host the world's biggest annual internet event, or that CEOs of global tech giants and the world's top robotics experts would flock there, should not surprise anyone. China is where the action is across an array of powerful internet-enabled technologies such as AI, robotics, fintech and e-commerce as well as virtual and augmented reality.

The Trump White House has devoted much of its first year to putting America first, cracking down on who can come into this country--from promising a wall along the US-Mexico border and the deportation of thousands of undocumented immigrants, to numerous attempts at a travel ban blocking entrance for people from several Muslim-majority countries. But under the America First banner, the administration has been quietly but vastly increasing hurdles in another area: for foreign nationals looking to live and work legally in the US. Since the spring, the Trump administration has introduced a number of administrative changes aimed specifically at increasing scrutiny on work visa applications. Issued through policy memoranda from United States Citizenship and Immigration Services (USCIS), the agency tasked with handling and adjudicating work and citizenship applications, the revisions have largely flown under the radar, as many of them have been incremental or seem innocuous on the surface. What's more, because a large number of the changes are adjustments to existing department policies or guidance, many have been able to go into effect immediately, without needing to undergo a formal rule proposal process or public comment period.