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[Event] Shanghai User Meetup Review

Posted 1 year ago
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All notebooks used in the presentation can be downloaded at the end of the post.

The idea of the post is to encourage our lovely users to share their experience about Wolfram products in local meetup groups, building up friendship and partnership among our community.

On 9/8/2018 Saturday, WRI Developer Mr. Shenghui Yang hosted a 12-people private Mathematica user panel to discuss the latest R&D achievement of Wolfram Language V11.1, 2 and 3, including

  • Updates and Improvements for Geo system and Entity
  • Neural Network in V11.3
  • Wolfram Cloud user interface and deployment
  • Several appealing examples of Mathematica dynamic feature in K-12 teaching project



Geo system

To have Wolfram Language features more accessible and relatable to our domestic users, Shenghui mixed his real life elements into Wolfram Language. The whole presentation became his daily life storytelling upon Wolfram Language knowledge base.

W|A command line interface briefly describes the weather condition on the day of this event


GeoMagenetData and GeoGravityData demonstrates important geophysics properties of Shanghai at the moment of the presentation ;-) No need to worry about any anomaly


GeoPosition with customized GeoMarker visualize the location of this event along the riverband of Yangtze


GeoDistance, GeoPath and several powerful projection options show our user how Wolfram headquarters relates to the meeting place. One of ~530 projection types is used in the example.

    In:= GeoProjectionData["LambertAzimuthal"]
    Out= {LambertAzimuthal,{Centering->{0,0},GridOrigin->{0,0},ReferenceModel->1}}

    In := GeoProjectionData[]//Short
    Out:= {Airy,Aitoff,Albers,AmericanPolyconic,ApianI,<<525>>,WinkelTripel}


GeoArea + GeoPosition, after mark the places the host visited most frequently in Shanghai, formed a large triangle. Combine EntityValue and related functions to easily extract the ratio of the triangle to Shanghai in terms of area


GeoPath and TravelDirectionData also reported accurately how long it takes to route and visit all three marked places


Finally, Shenghui mention that this event being hosted in a nice tea house, owned by YueSheng Du, the Shanghai-born Mob King and the God of Father of Far East during the Chiang Kai-shek era. Related background information can be retrieved both by built-in Entity functions and ExternalService with BingSearch V5



Discussion on K-12 Math Topics

This section is set specifically to users in K-12 education industry or the parents, whose kids in this academic interval, looking for new way for their kids to understand the school materials.

Shenghui and several local users reached out to some domestic teachers in public and private schools, ranging from the elite to mid level.

Real test problems were collected for the demo. A brief moment was left to the audience to think about the challenging problems before seeing the notebook with solution. The solution uses Mathematica built-in strong visualization, dynamic and CloudDeploy features. One of the most stressful and painful problem in the current domestic K-12 math education is that students need to take math-olympiad level exam for middle and high school. Most of the kids have no choice but to recite the hard-coded hacks to solve the tricky problems in short time. Lack of understanding and intuitive explanation make the process even more challenging. The host brings new vision into these problem via graphical presentation.

Here is an example of Non-stop trains problem with graphical explanation. (10 grade math problem) This question is asked to compute the distance between each cross point. The demo is designed to help students to understand the physical process and solve by hand in the exam, rather than shoot a Mathematica solution to them



Neural Network and AI

The presentation is based on the updated version of Taliesin's notebook and demo session on YouTube (some NN layers' name are updated in V 11.3 like DotPlusLayer -> LinearLayer). The examples are fully tested in the attached notebook for V11.3. Though the topic is quite involved for first time users, the audience are willing to learn Wolfram Language. Shenghui and his college roomate, a Tecent AI Lab senior researcher and also a veteran Mathematica user, collaboratively initialize bi-weekly online discussion for domestic Mathematica users. The one-hour AI-topic paper reading session is aimed to have the users familiar with basic NN layers in Wolfram Language and with different Networks available in the Wolfram Neural Network Repository.

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