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Welcome to 2017 with 3 Data Science Talks

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  • Join us back at out spiritual home for our first event of 2017.

    There will be the usual beer 'n' pizza, networking and 3 x 25 minute talks.


    Schedule

    6pm: Arrival. Please help us set up the chairs so we can start asap - then grab a drink from the fridge and a slice or two of pizza.

    6:30: Intro and first talk

    7:15 break

    7:30 talks 2 & 3

    8:30 finish off the drinks and help tidy up.

    9:00 close and head off to the Post Office Hotel ??



    Talk 1 - Joost van der Linden

    From student to 'scientist' - Starting out in data analytics

    Working towards a PhD while simultaneously being employed as a "junior" data scientist has provided me with insights on what it's really like to progress from learning about data science to actually doing it yourself. You undoubtedly will have heard, or experienced, that learning and doing are not the same, but what is the actual difference in our sector? How do you go from writing assignments to communicating your data insights to your colleagues? What challenges will you face? In this talk, I will draw on my experiences of working with government and not-for-profit data to answer these questions and provide students and aspiring data scientists with a head start.


    Joost van der Linden is a PhD student in Engineering at The University of Melbourne and a part-time data scientist at Our Community. Before settling Down Under, Joost obtained a BSc and MSc in Applied Mathematics from the Delft University of Technology in The Netherlands, and worked for IBM Research in America and for Schlumberger in England. Currently, he analyses grants and donation data for Our Community, a B-Corporation providing advice, connections, training and tech tools for not-for-profits and other organisations working to build stronger communities. Joost is also the founder and co-organiser of the yearly Melbourne Datathon.


    Talk 2 - Marco Lui & Marton Bodonyi

    Using Data Science To Reach 10 Million Visitors Per Month

    Melbourne-based transit search and booking site, Rome2rio, attracts up to 10 million visitors each month. In this talk, team members Marco Lui and Marton Bodonyi will share insights into using data science to drive your advertising strategy, to extract usable data on trends and patterns in your website traffic, to understand where you should be testing new UX functionality, and to delve into the complexities of A/B testing in a high-traffic consumer site.

    Marco Lui completed a PhD in the Natural Language Processing group at the University of Melbourne in 2015, supervised by Tim Baldwin. He joined Rome2rio in October 2014, where he’s been working as a Data Scientist / Software Engineer. He is responsible for a diverse range of data-intensive analysis and engineering tasks.

    Marton Bodonyi is a software engineer working in Melbourne at Rome2rio. He has over 6 years experience working in London and Melbourne on digital products and has recently started UsableTravel, a blog that discusses UX in the context of the travel industry.


    Talk 3 - Clement Fredembach

    Social Networks Analytics decoded and predicting deaths in Game of Thrones


    This talk will use the book/television phenomenon to shed light into three problems often encountered in Advanced Analytics:
    1. How to extract meaningful information from large text documents (e.g., contracts, books)
    2. How to construct accurate social networks from text information
    3. How to use Social Network Analytics (SNA) in conjunction with other propensity models to make accurate predictions

    Using the 'Game of Thrones' book series, this session will introduce the analysis to:
    • automatically parse and structure information to generate accurate social network of characters as the story develops; and
    • make inferences on future character deaths using belief propagation across networks.

    Combining the models allowed Clement to predict future death events with truly remarkable accuracy, demonstrating the predictive power of SNA alone and in conjunction with classical propensity models.

    Clement Fredembach is a data scientist with Teradata Australia and New Zealand Advanced Analytics group. With a background in Colour Science, Computational Photography and Computer Vision, Clement has designed and built perceptual statistical experiments and models for the past 10 years.

    Clement strives to combine his psychometric, perceptual and statistical knowledge to deliver insights and their story that are understandable and actionable to non-technical audiences.

    Prior to joining Teradata, Clement collaborated with several Fortune 500 and academic institutions as a researcher, publishing and patenting large portions of of his research along the way.

    Clement holds an MSc in Communication Systems from EPFL (Switzerland) on Image Classification and a PhD from UEA (UK) on Computational Imaging. His interests range from behavioral psychology to graph theory and photography.

Join or login to comment.

  • Rafał

    As a person who is halfway through Andrew Ng's Machine Learning course, I couldn't agree more

    1 · Yesterday

    • Spira S.

      Also agreed. I started with Andrew Ng's course. The guy is one of the best lecturers ive come across; awesome guy. After I completed the course I started re-writing the examples in R, which then led me to build some predictive models at work (I find you do you best learning with a real problem). I also rely on R-blogger a lot for inspiration.

      2 · Yesterday

  • Udaya R.

    Data science seems vast. What is your suggestion for a beginner to get started?

    2 · January 4

    • Chris

      According to my experience so far, I would recommend Andrew Ng's Coursera course is the best place to start. Then, you can figure out yourself where you should look into next. Also, reading papers and replicate them in the simulation environment will be very helpful to sharpen your skills even further.

      1 · Yesterday

    • Arran S.

      I'll add to look out for startups or companies who will support you exploring new tools.

      Yesterday

  • Rafał

    Hi Phil,
    Any chance of a next-door room with a live feed monitor, given the number of people on the waiting list? Btw, if anyone can't make it , I'll be happy to take your seat. Cheers

    2 · February 10

    • Iain S.

      Sounds a fair solution for me Phil and lots of others too. But a shame that people for whom this is a nontrivial amount of money, will be put off.

      2 days ago

    • Carly

      It would be great with the high waitlist to record the session if possible?

      1 · 2 days ago

  • Iain S.

    Hi Phil, do you know if this will be recorded?

    1 · 2 days ago

    • Phil B.

      Hi Iain,
      Unfortunately not. We did record our early talks and have our own youtube channel, but not many people watched them :-(

      2 days ago

    • Iain S.

      Ok, thanks Phil (Shame - But, understood!)

      2 days ago

  • Mai Thanh N.

    Do I have to pay for ticket? Excuse me. I'm a newcomer. I don't know much about this. Thank you!

    2 days ago

    • Phil B.

      Hi Mai,
      Welcome to the group. Our events are free unless otherwise specified. They do fill up quickly though and unfortunately this one is already full.

      2 days ago

  • Quen

    Unfortunately I got some conflicting schedule from work, so I now can't attend the talk this Thursday. I already updated my RSVP accordingly. Apology to all.

    2 days ago

  • Justin W.

    Hi, we're looking to hire people who are passionate about data science. What's the best way to share what we are offering - I'm mindful that I don't want to spam your stream!

    2 · February 8

    • Phil B.

      Hi Justin,

      Please use the dedicated jobs discussion forum to post jobs ads.

      https://www.meetup.com...­

      You may also be interested in our internship program which will be running this year as part of the Melbourne Datathon. You can register your interest at

      http://www.datascienc...­

      Phil

      2 · February 8

    • Justin W.

      Thanks Phil, very useful!

      February 9

  • Iain S.

    Hi Udaya, see how you find Hadley Wickham's upcoming book - whole thing is free online: http://r4ds.had.co.nz/

    I learnt a lot from
    (1) Coursera.org's 'Introduction to Data Science' MOOC
    (2) the Data Science Short Course from Data Science Melbourne

    2 · January 5

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