In doing so, you learn to work with lists and use the power of sentiment analysis in the Wolfram Language. In Sentimental 8-Ball, you create a Magic 8-Ball that picks its answers based on how positive or negative the mood of the user’s question seems. This is not only a pretty cool way to learn about things like time zones, but also shows you how to use geographic data and create an interactive experience in the Wolfram Language. In the day and night tracker project, you create a program that gives you a real-time view of where the sun is up right now and lets you check whether it’s day or night time in a particular country. It also introduces you to creating interfaces and controls for your projects, choosing random outcomes, and displaying images with the Wolfram Language. The coin and dice project shows you how to create a coin toss and dice roller that you can use to move your favourite board game into the digital age. I tried this out with my own CoderDojo club and it got a very positive reception, even if Dublin weather usually does report rain! Coin and dice My favourite of the new projects is the weather dashboard which, in a few quick steps, teaches you to create this shiny-looking widget that takes the user’s location, finds their nearest major city, and gets current weather data for it. If you’d like to learn more about the Wolfram Language on the Raspberry Pi, check out this great blog post written by Lucy, Editor of The MagPi magazine! Weather dashboard The language does a lot of the heavy lifting for you and is a great way to let young learners in particular work with data to quickly produce real results. The Wolfram language is particularly good at retrieving and working with data, like natural language and geographic information, and at producing visual representations with an impressively small amount of code. Try out the Wolfram Language today, available as a free download for your Raspberry Pi (download details are below). The system uses classical functions to interpolate the dynamic pressure changes around the airplane axes then, through several layers of Wolfram’s automatic machine learning framework, it assesses when LOC is imminent and instructs the user on the proper countermeasures they should take.We’ve worked alongside the team at Wolfram Mathematica to create ten new free resources for our projects site, perfect to use at home, or in your classroom, Code Club, or CoderDojo. Using sensors to detect changes in the acceleration and air pressure, the system calculates the probability of each data point (an instance in time) to be in-family (normal flight) or out-of-family (non-normal flight/possible LOC event), and issues the pilot voice commands over a Bluetooth speaker. FOALE AEROSPACE’s system, which it calls the Solar Pilot Guard (SPG), is a solar-charged probe that identifies and helps prevent loss-of-control (LOC) events during airplane flight. All their development work was done in-house, mainly using the Wolfram Language running on the desktop and a Raspberry Pi. Mike is a man of many talents (pilot, astrophysicist, entrepreneur) and has spent an amazing 374 days in space! Together with Jenna (who is currently finishing her PhD in computational fluid dynamics), he was able to build a complex machine learning system at minimal cost. The system is marketed as a DIY kit for aircraft hobbyists, but the ideas it’s based upon can be applied to larger aircraft (and even spacecraft!).įOALE AEROSPACE is the brainchild of astronaut Dr. For the past two years, FOALE AEROSPACE has been on an exhilarating journey to create an innovative machine learning–based system designed to help prevent airplane crashes, using what might be the most understated machine for the task-the Raspberry Pi.
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