Jeremy Tillman gives a presentation on using multicolumn joins in Django. He discusses modeling poll and choice data across multiple customers. By adding a customer ID field to polls and choices and defining a ForeignObject, data can be colocated and queries can filter across multiple fields like customer and poll together. This improves performance over traditional foreign keys when data is partitioned across columns. ForeignObject allows defining multicolumn relationships and querying across those fields in Django.
Innovation in Human-Machine Interaction
Agenda:
5:45 - 6:00: Welcome & Networking
6:00 - 6:15: News and Introduction
6:15 – 7:00: The value of applied research in human-system interaction in B2B environment
7:00 - 7:30: Panel: Review of new human-system interaction seen at CHI 2018
7:30 - 8:00: Networking
A recommendation engine for your applications - M.Orselli - Codemotion Rome 17Codemotion
Nowadays a lot of websites try to guess what we could like: "Recommendation for you in books" "People you may like" Sounds familiar, isn't it? Wouldn't be cool if you could do the same in your application? Well, this session is for you! In the first part of this talk recommendation systems will be introduced, focusing on collaborative filtering algorithms (CR). After that we'll dive in Prediction.io, an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
Innovation in Human-Machine Interaction
Agenda:
5:45 - 6:00: Welcome & Networking
6:00 - 6:15: News and Introduction
6:15 – 7:00: The value of applied research in human-system interaction in B2B environment
7:00 - 7:30: Panel: Review of new human-system interaction seen at CHI 2018
7:30 - 8:00: Networking
A recommendation engine for your applications - M.Orselli - Codemotion Rome 17Codemotion
Nowadays a lot of websites try to guess what we could like: "Recommendation for you in books" "People you may like" Sounds familiar, isn't it? Wouldn't be cool if you could do the same in your application? Well, this session is for you! In the first part of this talk recommendation systems will be introduced, focusing on collaborative filtering algorithms (CR). After that we'll dive in Prediction.io, an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery.
The UX of AI Matters : How does the visual representation of a recommendation...Pierre-Majorique Léger
Meetup presentation at JDA of our paper presented at CHI 2018.
Abstract : Artificial intelligence (AI) based recommendation agents (RA) can help managers make better decisions by processing a large quantity of decision relevant information. Research on user-RA interactions show that users benefit from RA, but that there are some challenges to their adoption. For instance, RA adoption can only happen if users trust the RA. Thus, this study investigates how the richness of the information provided by an RA and the effort necessary to reach this information influence users' perceptions and usage. A within-subject lab experiment was conducted with 20 participants. Results suggest that perceptions toward the RA (trust, credibility, and satisfaction) are influenced by the RA information richness, but not by the effort needed to reach this information. In addition to contributing to HCI literature, the findings have implications for the design of better AI-based RA systems.
Open access paper : https://dl.acm.org/citation.cfm?id=3188639
Should we continue investing in our game? This is an essential and challenging question for all the game producers and publishers. Answering this question based on data is the most assured solution, but data analysis always has its own challenges such as: • What kind of data and what amount of data is valid for making decisions? • Which target audience and what kind of tests can give us insights? • Which version of our game is finalized enough to be tested? • How can we assign KPIs to our games? A successful game is consisted of three connected key parts: I. Attraction: Fun core game mechanics II. Engagement: Addictive core loop and meta game III. Monetization: Solid Monetization strategy For answering these questions, in Medrick Game Studio we have designed a chain of instructions: Step 1: Game Concept Step 2: Session Design Step 3: Prototype Step 4: Extended Prototype Step 5: Data Design Other topics that will be discussed are: • Soft launch proposes and attributes • Tests process • Iterations • User segmentation • PRM: Player Relationship Management • Tools
AYO Social Enterprise x EdgeX Social IdeathonJayren Teo 张健荣
In conjunction with Global Entrepreneurship Week (GEW) - AYO Social Enterprise partnered with EdgeX (GEW Singapore Host) to organise a Social Ideathon on 19th November 2019.
Lots of entrepreneurs struggle to explain their product in a clear and concise way. Then, they often don't know how to work with designers and developers since they don't speak their language. The role of a good entrepreneur is to break those barriers when it comes to his product.
In this workshop, you will go through important steps in the conception of a technical product:
• Product pitch: your product's vision
• Mockup: your product's design
• Database: your product's architecture
• User stories: your product's features
Remote, fast, accurate, distributed team decisionsIain Burns
A new and unique tool and service. Helps remote teams spread across a country or the World to come to a consensus decision on relative priorities very quickly. Up to 10 team members or sub-groups can prioritise up to 7 projects/areas.
Each team member inputs their views by a simple point and click method during a 30 minute one-on-one webcall with specialists. No data entry required from team. A detailed and highly accurate model is produced of the team view, taking every team members input into account.
Multiple outputs are generated in a report and team presentation via a webcast the next day. What-if models and different scenarios can then be tried out to tune the team choices.
The base presentation file for my 8-hour mini-course @CafeIT of Fanap about gamification. I took some steps further from just introducing the gamification and talked about the basic needs for designing a gamification solution.
A recommendation engine for your applications phpdayMichele Orselli
Nowadays a lot of websites try to guess what we could like: ”Recommendation for you in books” or ”People you may like”. Sounds familiar, isn’t it? Wouldn’t be cool if you could do the same in your application? Well, this session is for you! In the first part of this talk, recommendation systems will be introduced, focusing on collaborative filtering algorithms (CR). After that we’ll dive in Prediction.io, an open source machine learning server for software developers to create predictive features, such as personalization, recommendation, and content discovery. In the last part, we’ll cover the integration details with a PHP application.
How to boost learning effectiveness and employee engagement at the same time?
Change your organization learning forever through game-based learning.
www.greenbookslearning.com
Selling Insurance: Have You Modernized? [Infographic]Hearsay Systems
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Meetup presentation at JDA of our paper presented at CHI 2018.
Abstract : Artificial intelligence (AI) based recommendation agents (RA) can help managers make better decisions by processing a large quantity of decision relevant information. Research on user-RA interactions show that users benefit from RA, but that there are some challenges to their adoption. For instance, RA adoption can only happen if users trust the RA. Thus, this study investigates how the richness of the information provided by an RA and the effort necessary to reach this information influence users' perceptions and usage. A within-subject lab experiment was conducted with 20 participants. Results suggest that perceptions toward the RA (trust, credibility, and satisfaction) are influenced by the RA information richness, but not by the effort needed to reach this information. In addition to contributing to HCI literature, the findings have implications for the design of better AI-based RA systems.
Open access paper : https://dl.acm.org/citation.cfm?id=3188639
Should we continue investing in our game? This is an essential and challenging question for all the game producers and publishers. Answering this question based on data is the most assured solution, but data analysis always has its own challenges such as: • What kind of data and what amount of data is valid for making decisions? • Which target audience and what kind of tests can give us insights? • Which version of our game is finalized enough to be tested? • How can we assign KPIs to our games? A successful game is consisted of three connected key parts: I. Attraction: Fun core game mechanics II. Engagement: Addictive core loop and meta game III. Monetization: Solid Monetization strategy For answering these questions, in Medrick Game Studio we have designed a chain of instructions: Step 1: Game Concept Step 2: Session Design Step 3: Prototype Step 4: Extended Prototype Step 5: Data Design Other topics that will be discussed are: • Soft launch proposes and attributes • Tests process • Iterations • User segmentation • PRM: Player Relationship Management • Tools
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In conjunction with Global Entrepreneurship Week (GEW) - AYO Social Enterprise partnered with EdgeX (GEW Singapore Host) to organise a Social Ideathon on 19th November 2019.
Lots of entrepreneurs struggle to explain their product in a clear and concise way. Then, they often don't know how to work with designers and developers since they don't speak their language. The role of a good entrepreneur is to break those barriers when it comes to his product.
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• Product pitch: your product's vision
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• Database: your product's architecture
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A new and unique tool and service. Helps remote teams spread across a country or the World to come to a consensus decision on relative priorities very quickly. Up to 10 team members or sub-groups can prioritise up to 7 projects/areas.
Each team member inputs their views by a simple point and click method during a 30 minute one-on-one webcall with specialists. No data entry required from team. A detailed and highly accurate model is produced of the team view, taking every team members input into account.
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The base presentation file for my 8-hour mini-course @CafeIT of Fanap about gamification. I took some steps further from just introducing the gamification and talked about the basic needs for designing a gamification solution.
A recommendation engine for your applications phpdayMichele Orselli
Nowadays a lot of websites try to guess what we could like: ”Recommendation for you in books” or ”People you may like”. Sounds familiar, isn’t it? Wouldn’t be cool if you could do the same in your application? Well, this session is for you! In the first part of this talk, recommendation systems will be introduced, focusing on collaborative filtering algorithms (CR). After that we’ll dive in Prediction.io, an open source machine learning server for software developers to create predictive features, such as personalization, recommendation, and content discovery. In the last part, we’ll cover the integration details with a PHP application.
How to boost learning effectiveness and employee engagement at the same time?
Change your organization learning forever through game-based learning.
www.greenbookslearning.com
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𝐓𝐉 𝐂𝐨𝐦𝐬 provides unlimited package services including such as Event organizing, Event planning, Event production, Manpower, PR marketing, Design 2D/3D, VIP protocols, Interpreter agency, etc.
Sports events - Golf competitions/billiards competitions/company sports events: dynamic and challenging
⭐ 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐝 𝐩𝐫𝐨𝐣𝐞𝐜𝐭𝐬:
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What might I learn?
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Who might benefit? Anyone and everyone leading folks from the shop floor to top floor.
Dr. William Harvey is a seasoned Operations Leader with extensive experience in chemical processing, manufacturing, and operations management. At Michelman, he currently oversees multiple sites, leading teams in strategic planning and coaching/practicing continuous improvement. William is set to start his eighth year of teaching at the University of Cincinnati where he teaches marketing, finance, and management. William holds various certifications in change management, quality, leadership, operational excellence, team building, and DiSC, among others.