Worcester Polytechnic Institute: Helping to Make Math “Graspable,” WPI Researchers Guide Design of Algebra Tool for Students and Teachers

Worcester Polytechnic Institute: Helping to Make Math “Graspable,” WPI Researchers Guide Design of Algebra Tool for Students and Teachers. “Researchers at Worcester Polytechnic Institute (WPI) have received a $185,085 subcontract for the second phase of design development and testing of Graspable Math, a digital platform that helps students learn algebra…. Students have traditionally worked algebraic equations by making notations on paper, but Graspable Math puts algebra onto tablet and laptop screens. Students click on or swipe numbers and symbols to solve equations and get instantaneous feedback on their actions, while teachers can monitor their work.”

Lifehacker: Use Wolfram Alpha to Conceptualize Giant Numbers

Lifehacker: Use Wolfram Alpha to Conceptualize Giant Numbers. “Our monkey brains didn’t evolve to understand big numbers without some help. So when you run into an abstract figure, it’s good to have some real-world thing to compare it to. That’s why I memorize a few stats about the U.S. population; that’s why we made a video comparing Jeff Bezos’s money to Beyoncé’s. When you need to visualize a certain number, large or small, search it on Wolfram Alpha, and you’ll get a comparison to some real-world objects.”

Wolfram Blog: The New World of Notebook Publishing

Wolfram Blog: The New World of Notebook Publishing. “Wolfram Notebooks on the Web
We’ve been working towards it for many years, but now it’s finally here: an incredibly smooth workflow for publishing Wolfram Notebooks to the web—that makes possible a new level of interactive publishing and computation-enabled communication.”

Code (Love): 21 Resources To Learn Mathematics For Machine Learning

Code (Love): 21 Resources To Learn Mathematics For Machine Learning. “It can be difficult at times to understand what’s going on with machine learning and to understand what mathematics for machine learning really means. This is due to the emergence of machine learning libraries and programming frameworks that take care of the mathematical and statistical logic. Anybody who works with machine learning needs to understand the mathematics and statistics of machine learning. Here’s a list of handy resources split by topic to address that need.” Annotation a little sparse at times, but an extensive list.

ProBeat: Wolfram’s natural language understanding looks incredibly useful (VentureBeat)

VentureBeat: ProBeat: Wolfram’s natural language understanding looks incredibly useful. “Wolfram Research yesterday launched Wolfram Alpha Notebook Edition for Windows, Mac, and Linux. The news largely flew under the radar, which is frankly a shame. The new tool combines Wolfram Alpha and Mathematica to give students (and teachers) a new way to build through whole computations. But it’s the natural language understanding (NLU) examples that really caught my eye.”

Enhanced Step-by-Step Solutions Now on Mobile: Announcing Wolfram|Alpha 2.0 for iOS (Wolfram Blog)

Wolfram Blog: Enhanced Step-by-Step Solutions Now on Mobile: Announcing Wolfram|Alpha 2.0 for iOS. “In October 2009, a few months after the website launched, we released Wolfram|Alpha 1.0 for the iPhone. Today, we are announcing the latest evolution in Wolfram|Alpha for your iOS phone or tablet, Version 2.0, which is available now on the iOS App Store.”