Trondheim Developer Conference

DND (Dataforeningen) Trondheim inviterer til TDC Aspire, et arrangement for studentmedlemmer. I år inviterer vi 200 studenter gratis til å delta på Trondheim Developer Conference fra kl. 13:00 til 17:00. Dere får streaming av foredrag, og servert lunsj. I pausene er det fritt frem å mingle med bedriftene som står på stands. Det er store muligheter for at du møter din fremtidige arbeidsgiver.

TDC Aspire er et samarbeid mellom linjeforeningene og DND Aspire. Konferansen og TDC Aspire går av stabelen mandag 30. Oktober i 2017 på Clarion Brattøra hotell og konferansesenter.

Trondheim Developer Conference (TDC) er Midt-Norges største møteplass for utviklere. I 2016 var det 800 deltakere og på scenen møtte du store navn som Scott Hanselman. Dette er det andre av en rekke arrangement, hvor DND Trøndelag leverer faglig innhold og mingling med ulike bedrifter.

Vil du vite mer om TDC? Sjekk ut http://trondheimdc.no eller https://www.facebook.com/TDConf/

Program

13:00 Registrering ved konferanseinngang

13:10 Intro & lunsj i livingroom

13:15-14:00 Foredrag 1: How do we know that we know? Jo Røislien

14:00-14:15 Pause og mingling på stands

14:15-14:45 Foredrag 2: Machines are learning wind power forecasting, Boris Tistan

14:00-14:15 Pause og mingling på stands

15:00- 15:30 Foredrag 3: Artificial intelligence at Telenor Research, Axel Tidemann

15:30-15:45 Pause og mingling på stands

15:45-16:15 Foredrag 4: Data Driven Conversation, Joshua Newnham

16:15-16:30 Info, trekking av vinnere og takk for i dag fra arrangørene

16:30-17:00 Foredrag 5: Agile experiments in Machine Learning with F#, Mathias Brandewinder

17:00-17:15 En siste runde på stands for de som vil det

17:15-18:00 Siste foredrag for de som vil(anbefales): Algorithms to Live By: The Computer Science of Human Decisions, Brian Christian

Mer informasjon om foredragene:

How do we know that we know?

Name: Jo Røislien

Time: 13:15

Talk

We humans hunt for meaning in life and a reason to why we are here. Jo Røislien takes us all through subjects from the challenges with our hunt for meaningfulness, to Florence Nightingale, the american presidential election, vikings, space, salmon and mentos.. Is more information always better? Are really 'Big Data' the answer, or just a new question in itself?

Audience

No code

About Jo Røislien

Jo Røislien is one of Norway's most prominent research and science lecturers. He loves numbers, has the hair of a Norwegian troll, drinks (instant) coffee with milk and thinks yesterday is greatly overrated. While other researchers lecture in tired classrooms and lecture halls, Jo lectures on TV. He was the presenter and scriptwriter for the successful mathematical TV series "Siffer" at NRK1 in the fall of 2011, and in autumn 2012 he was the first Norwegian presenter on the Discovery Channel. Jo has a PhD in Statistics from NTNU and cooperates with a number of medical research communities across the country. He is currently Associate Professor in Statistics at the University of Stavanger and Senior Researcher at the Faculty of Medicine at the University of Oslo. He has written several books, including "Tall forteller" with statistics researcher Kathrine Frey Frøslie and "Siffer" together with copywriter Magnus Nome.

Machines are learning wind power forecasting

Name: Boris Tistan

Time: 14:15

Talk

The main goal of this talk is to show how rapidly can surprising results be reached when Artificial intelligence is applied to wind power forecasting problem, how do you approach such a problem, and operationalise the machine learning model to bring real business difference. We will take closer look not only on tools and practices, but also why current approaches were not that successful, and what made this approach work.

Audience

Interesting content for both ML and renewable energy fans, the talk is more about the approach to the problem than concrete technologies, but I might include slices of code to pinpoint ease of use of certain open source libraries.

About Boris Tistan

I'm data science expert working in Powel, Trondheim based software company that provides solutions to high majority of energy producers in Nordics. I hold master degree in Artificial Intelligence, and I've worked on multiple applications of Machine learning in energy sector, including Electricity consumption forecast, Wind and Solar power forecasting and other big data applications. I'm very passionate about innovative technologies and environment, and this case was a perfect marriage of those two. I always talk too much and rarely stick to the script, but my goal is to engage the audience and try for them to share my passion.

Artificial intelligence at Telenor Research

Name: Axel Tidemann

Time: 15:00

Talk

The talk will give an introduction to how we work with artificial intelligence at Telenor Research.

Audience

Everyone with an interest for machine learning and AI.

About Axel Tidemann

Axel Tidemann has a PhD in artificial intelligence from NTNU. He is a research scientist at Telenor Research, where he works with deep learning to understand images, text and sequences.

Data Driven Conversation

Name: Joshua Newnham

Time: 15:45

Talk

Chatbots are disrupting industries in the same way the web and mobile revolutions did - this is leading to a change in the way customers engage with brands and vis-versa. In order to deliver a compelling experience we must overcome many technical and design challenges; in this talk we make a start by exploring some ways of teaching chatbots to better engage with humans using human language in ways that appear seamless and natural to humans. Unlike techniques commonly used today, which rely on dialog systems built using hand-crafted rules and templates, we explore techniques that are driven by data and advancements made in Artificial Intelligence.

Audience

An interest in chatbots and AI (machine learning) is required but everything will be explained in, hopefully, just enough detail for designers and developers to understand and get something out of the talk.

About Joshua Newnham

Lead Design Technologist at Method; working on designing and building digital solutions that make our lives a little easier and more enjoyable.

Agile experiments in Machine Learning with F#

Name: Mathias Brandewinder

Time: 16:30

Talk

Just like traditional applications development, machine learning involves writing code. One aspect where the two differ is the workflow. While software development follows a fairly linear process (design, develop, and deploy a feature), machine learning is a different beast. You work on a single feature, which is never 100% complete. You constantly run experiments, and re-design your model in depth at a rapid pace. Traditional tests are entirely useless. Validating whether you are on the right track takes minutes, if not hours. In this talk, we will take the example of a Machine Learning competition we recently participated in, the Kaggle Home Depot competition, to illustrate what "doing Machine Learning" looks like. We will explain the challenges we faced, and how we tackled them, setting up a harness to easily create and run experiments, while keeping our sanity. We will also draw comparisons with traditional software development, and highlight how some ideas translate from one context to the other, adapted to different constraints.

Audience

No preliminary knowledge of machine learning or F# necessary. Expect some live coding!

About Mathias Brandewinder

Mathias Brandewinder has been developing software on .NET for about 10 years, and loving every minute of it, except maybe for a few release days. His language of choice was C#, until he discovered F# and fell in love with it. He enjoys arguing about code and how to make it better, and gets very excited when discussing TDD or F#. His other professional interests include forecasting models, machine learning and applying math to solve business problems. Mathias is a Microsoft F# MVP and the founder of Clear Lines Consulting. He is based in San Francisco, blogs at www.clear-lines.com/blog

Algorithms to Live By: The Computer Science of Human Decisions

Name: Brian Christian

Time: 17:15

Talk

There is a particular set of problems that all people face, problems that are a direct result of the fact that our lives are carried out in finite space and time. What should we do, or leave undone, in a day or a lifetime? What degree of mess should we embrace—and how much order is excessive? What balance between trying new things and enjoying our favorite ones makes for the most fulfilling life? These might seem like problems unique to humans; they're not. For more than half a century, computer scientists have been grappling with, and in many cases solving, the equivalents of these everyday dilemmas. From finding a spouse to finding a parking spot, from organizing our inbox to predicting the future, the solutions they’ve found have much to teach us. Learning to recognize the underlying algorithmic structure of the world around us gives us the tools to transform the wisdom of computer science into strategies for human living.

Audience

No code

About Brian Christian

Brian Christian is the author of The Most Human Human, which was named a Wall Street Journal bestseller and a New Yorker favorite book of the year, and has been translated into ten languages. He is the coauthor, with Tom Griffiths, of Algorithms to Live By, a #1 Audible bestseller, Amazon best science book of the year and MIT Technology Review best book of the year.

Konkurranse

Muligheter for å vinne fete premier hvis man finner alle svarene på spørsmål om de ulike bedriftene på stand. Mer informasjon om konkurransen blir sendt ut på mail til de som får plass.

Dersom du kommer deg igjennom alle stands på TDC og finner svarene på spørsmålene var man i fjor med i trekningen av:

3 Chomebooks, 6 Raspberry Pi Starter Kit og 10 Powerbanks

Årets premier publiseres straks.

Kart: http://i.imgur.com/QdTKOUV.png