Clustering is the grouping of objects together so that objects belonging in the same group (cluster) are more similar to each other than those in other groups (clusters). In this intro cluster analysis tutorial, we'll check out a few algorithms in Python so you can get a basic understanding of the fundamentals of clustering on a real dataset. For the clustering problem, we will use the famous Zachary's Karate Club dataset. The story behind the data set is quite simple: There was a Karate Club that had an administrator "John A" and an instructor "Mr. Then a conflict arose between them, causing the students (Nodes) to split into two groups.

Pretty much every data rookie starts with Excel. It is a wonderful program for storing, cleaning and analysing (yes, you read that correctly) your data. Strictly speaking, Excel isn't free, but really – who pays for it these days? If you buy a Windows PC or laptop it'll usually come pre-installed, and if you get a new PC at work your employer will have it pre-installed for you. If you're prepared to look the other way, there are guys who know guys who can get you a copy that fell off the back of a lorry, but I wouldn't endorse that.

The ultimate aim of any Financial Institution (FI) is to earn the confidence and faith of their customers but equally important to verify the information customers provide back to them. The regulators are increasingly concentrating on ensuring that banks have robust and effective controls in place for customer due diligence (CDD). Multinational banks need to ensure compliance not only in their home country but also in environments that are more complex and have fewer infrastructures. For Example, Deloitte has highlighted in its "Meeting new expectation" report that AML sanctions-related fines and penalties imposed in 2013 and 2014 quadrupled the total for the previous nine years. Artificial Intelligence (AI) takes KYC and AML compliance to the next level.

Facebook's chatbots are learning the art of the deal, bartering and deceiving their way to better terms in negotiations with humans and other bots. Artificial intelligences that can negotiate effectively would make useful virtual assistants, says Mike Lewis at Facebook's research lab. Bots could be left to arrange appointments for people, sorting out calendar clashes by themselves. Or they could negotiate with several agents at once to book a holiday or make a purchase on your behalf. Most existing bots – such as Apple's Siri or those built into chat apps like Facebook Messenger – may be able to get you a taxi or order a pizza but they can't engage in complex negotiations, says Lewis. If we want bots to help us with more complex tasks they need to become dealmakers, especially if the task involves cooperation or compromise, like negotiating the purchase or sale of a property, for example.

The world has more data than ever before. In fact, it's estimated that by 2020, we'll produce 44 zettabytes every day. One gigabyte can hold the contents of enough books to cover a 30-foot-long shelf. That's a lot of data -- too much for most companies to process. And yet front-line employees are still often left operating with data that's "too little, too late."

More than a third of U.S. jobs could be at "high risk" of automation by the early 2030s, a percentage that's greater than in Britain, Germany and Japan, according to a report released Friday. The analysis, by accounting and consulting firm PwC, emphasized that its estimates are based on the anticipated capabilities of robotics and artificial intelligence, and that the pace and direction of technological progress are "uncertain." It said that in the U.S., 38% of jobs could be at risk of automation, compared with 30% in Britain, 35% in Germany and 21% in Japan. The main reason is not that the U.S. has more jobs in sectors that are universally ripe for automation, the report says; rather, it's that more U.S. jobs in certain sectors are potentially vulnerable than, say, British jobs in the same sectors. For example, the report says the financial and insurance sector has much higher possibility of automation in the U.S. than in Britain.

Chatbots, an AI summit for good, AI-based cancer therapies, and Kuri the home robot are making news in today's AI Minute. Apple's HomePod and watchOS4, telepresence bots and a fake-news finding chatbot are making news in today's AI Minute. Intel's views on and recent investment in self-driving cars, Stan - France's Robot Valet, and a $12 billion biotech startup regrowing hair, are making news in today's AI Minute. AI and money laundering, robot manners, how AI may help fight ALS, and nimble robots are making news in today's AI Minute. AlphaGo, the state of Massachusetts, Apple's iPhone, and Porsche are making news in today's AI Minute.

Everyone who gets going in Machine Learning (and Deep Learning) gets overwhelmed by the plethora of MOOCs available. Here, I try to give a comprehensive survey of such courses available freely on the internet. You can take this post as an complementary to this and this previous posts. I will try to highlight some important pointers such as the difficulty of the courses, the correct order in which these should to be completed, the right audience for these courses. You will get a feel of how these courses give you a stack of skills in your arsenal and how you can use them to develop practical machine learning systems.

Brolly's vision is to re-design the insurance user experience based on data analytics and a centralised approach to the UI/UX of insurance policies Brolly is the UK's first artificially intelligent insurance advisory application that delivers contextually relevant insights through web and mobile apps which enables customers to make informed decisions about their insurance. With Brolly, customers can better understand whether they're over insured or under insured and where they can get a better price for the cover they need. Brolly users only need to enter their information once, and purchasing new cover will be achieved with one simple tap. Brolly will also help you manage all your insurance policies in one place, and provide instant access to your documents, prices, and contact numbers, so they're always at hand when you need them. Brolly has started with a clean slate and is developing an insurance company for the digital age.

Wrangling a pig--even a virtual one--is much easier if you get a friend to help. This much seems clear from a contest organized by Microsoft researchers to test how artificially intelligent agents could cooperate to solve tricky problems. How best to cooperate with your pig-wrangling pal is another question. The competition addresses an area of artificial intelligence that has had relatively little attention so far. AI researchers often develop software capable of performing a specific human task, such as playing chess or Go, and then measure it according to its ability to defeat a human player.