The "10 Year Challenge" seems like any other social media challenge, however it may have a major effect in the world of facial recognition. The Challenge as it is now, is to post two pictures of yourself side by side. One of the pictures is from 2008 while the other is from 2018. Seems pretty harmless at first glance, however Fortune 500 adviser and tech writer Kate O'Neill had this to say on Twitter. Me 10 years ago: probably would have played along with the profile picture aging meme going around on Facebook and Instagram Me now: ponders how all this data could be mined to train facial recognition algorithms on age progression and age recognition Kate O'Neill With the growth of data mining and facial recognition software it will be interesting to see if this has any ef
"Serverless", The new Buzzword Is this the apocalypse for servers? Photo by Brock DuPont on Unsplash Now you can be serverless too! Why waste time and resources running your own servers when a company will gladly take over with their new "serverless" plan.Wait... Don't we already have and use the cloud?"Well yes, but this is completely different! It's serverless! What actually is it? Serverless is actually a subset of cloud infrastructure. The only real difference is serverless is the cloud as FaaS (Function as a Service). Which means you only pay for your actual usage and that depends on the resources you used and the time they were used for. The cloud you typically pay a subscription that gives you a set amount of time and compute power. Serverles
Cloud Gaming? In the past week, both Google and Microsoft have announced there cloud gaming projects. Google announced Project Stream, a game streaming service to play games via Chrome. Microsoft announced Project xCloud, a cloud platform that will allow gamers to play from anywhere they choose. Which will let gamers use their mobile phones to play. Project Stream Project Stream became available to test on October 5th 2018, with the first game on trial being Assassin's Creed Odyssey. In order to sign up you must be residing in the US and have a 25 Mbps connection, along with either Windows, Chrome OS, macOS, or Linux for the operating system. Common issues Reported from public testing:- Not getting 60fps- Minor lag/latency- Difficult to use touch interface controls, using a controller gi
Based on IBM's fictional data set created by their data scientists. Introduction: Employee Attrition is when an employee leaves a company due to normal means, (loss of customers, retirement, and resignation), and there is not someone to fill the vacancy. Can a company identify employee’s that are likely to leave a company? A company with a high employee attrition rate is a good sign of underlying problems and can affect a company in a very negative way. One such way is the cost related to finding and training a replacement, as well as the possible strain it can put on other workers that in the meantime have to cover. Preprocessing: This dataset was produced by IBM and has just under 1500 observations of 31 different variables including attrition. 4 of the variables (EmployeeNumber, Over18
Using Basic Data Analysis functions on the mtcars dataset Let's Start # Copying mtcars data frame to our new data frame myCarsmyCars <- mtcars Which car has the highest horsepower (hp) ? #find and display the car with the highest horsepower index <- which.max(myCars$hp)# Display the car name along with the rest of the row myCars[index,] ## mpg cyl disp hp drat wt qsec vs am gear carb ## Maserati Bora 15 8 301 335 3.54 3.57 14.6 0 1 5 8 Maserati Bora has the highest horsepower at 335 Exploring miles per gallon (mpg) of the cars # find and display the car with the highest mpgind...