Wolfram Computation Meets Knowledge

News, Views & Insights

Date Archive: 2019 January

Computation & Analysis

How I Became a Wine Expert Using the Wolfram Language

Do you select a bottle of wine based more on how fancy the sleeve is than its price point? If so, then you're like me, and you may be looking to minimize the risk of wishful guesses. This article may provide a little rational weight to your purchasing decisions.

Due to my research using the Wolfram Language, I can now mention the fact that if you are spending less than $40 on a random bottle of wine, you have a less than 0.1% chance of finding a 95+-rated wine. I could also perhaps reel off some flavors and characteristics of wines from Tuscany, for example—cherry, fruit, spice and tannins. My aim is to show you how I took a passing idea of mine and brought it to fruition using the Wolfram Language.

Jacob Wells, Technical Specialist, European Sales
Education & Academic

Teacher Resources for Introducing Computational Thinking and Data Science

As many teachers make the transition back into classes after the holidays, quite a few have plans to update lessons to include segments that introduce data science concepts. Why, you ask?

According to a LinkedIn report published last week, the most promising job in the US in 2019 is data scientist. And if you search for the top “hard skills” needed for 2019, data science is often in the top 10.

Data science, applied computation, predictive analytics... no matter what you call it, in a nutshell it’s gathering insight from data through analysis and knowing what questions to ask to get the right answers. As technology continues to advance, the career landscape also continues to evolve with a greater emphasis on data—so data science has quickly become an essential skill that’s popping up in all sorts of careers, including engineering, business, astronomy, athletics, marketing, economics, farming, meteorology, urban planning, sociology and nursing.

Kathy Bautista, Academic Programs & Initiatives
Computation & Analysis

Deploying and Sharing: Web Scraping with the Wolfram Language, Part 3

So far in this series, I’ve covered the process of extracting, cleaning and structuring data from a website. So what does one do with a structured dataset? Continuing with the Election Atlas data from the previous post, this final entry will talk about how to store your scraped data permanently and deploy results to the web for universal access and sharing.

Brian Wood, Technical Communications & Outreach Manager
Computation & Analysis

Trivial Pursuits: Applications and Diversions with the Wolfram Language

Mark Greenberg is a retired educator and contributor to the Tech-Based Teaching blog, which explores the intersections between computational thinking, edtech and learning. He recounts his experience adapting old game code using the Wolfram Language and deployment through the Wolfram Cloud.

Chicken Scratch is an academic trivia game that I originally coded about 20 years ago. At the time I was the Academic Decathlon coach of a large urban high school, and I needed a fun way for my students to remember thousands of factoids for the Academic Decathlon competitions. The game turned out to be beneficial to our team, and so popular that other teams asked to buy it from us. I refreshed the questions each year and continued holding Chicken Scratch tournaments at the next two schools I worked in.

Wolfram Blog Team