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Using Machine Learning & Statistics To Predict The US Presidential Election

The talk is on using Machine Learning & Statistics to make Predictions.

The speaker: Kazem Jahanbakhsh.

"How I Used Machine Learning & Statistics To Predict The US Presidential Election"

"US 2012 presidency election generated a large number of conversations in social networking websites such as Twitter. In September 2012, we started collecting & analyzing political tweets to see if we can find any interesting pattern/trend in the data. In particular, we were interested in the possibility of predicting US election result by analyzing tweets distributions. Our methodology was simple: (1) collect data, (2) use machine learning & statistics to analyze data, (3) visualize the results to get insight. This talk covers our methodology and some of our findings."

• 6:00PM Doors are open, feel free to mingle
• 6:30 Presentations start
• 8:00 Off to a nearby watering hole (Mr. Brownstone?) for a pint, food, and/or breakout discussions

Getting There

By transit there a number of high frequency buses (check Google Maps or the Translink site for your particular case) that will get you there. For the drivers, there is a fair bit of street parking (free and pay) in the area, especially after 6.


Bonus talk by Elena Popovici:

"Small Data, Rich Data: Exploratory Analysis and Visualization"

"Earlier this year, the US Medicare health organization (similar to the Canadian MSP, but mostly just for seniors) has released information about how much hospitals across the country charge the program. The dataset is relatively small and appears simple at first glance. Closer analysis reveals a rich structure and many peculiarities. Visualization plays a key role in exploring the nature of the data. The talk will cover approach, tools used (heavy on R and extensions) and findings."

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  • Elena P.

    Hi everyone, and Happy New Year!

    With apologies for the delay, here are the annotated slides, the recordings of my talk (curtesy of Saem, thank you!) and the interactive apps, all in one place:!datascience-meetup/c1wat


    January 13, 2014

  • A former member
    A former member

    Great presentations. Does anyone have the links to the slides?

    November 27, 2013

  • Master J.

    I'm also signed up to this in duplicate at DataScience?! I prefer to think of it as the more elite machine learning I'm interested in. I'm not only wondering if I should remove one of the RSVPs but which one, but if these groups are officially merged or will ever diverge in meetup event content variety, or not so then one should be taken down maybe? Also the datascience group is bigger so likely more stable and so the winner in which to phase out. Still again the elitism of this group seems more assuring in getting a seat. I think anyone in this group should be reminded of the datascience events only through a notification for each to signup for them there.
    What's the consensus on all this, your feedback please and thank you?

    November 7, 2013

    • Charles Iliya K.

      The 2 groups are NOT officially merged. When it makes sense to schedule the same event with both groups (because the topic is of interest to people who are interested in Machine Learning AND people who are interested in Data Science) we do. This will not always be the case though. (For example, a machine learning talk on the algorithmic concerns with ANNs on GPU hardware would make sense for the Machine Learning group, but probably not the Data Science group.) You are welcome to sign up with both groups with both groups, if you wish.

      1 · November 7, 2013

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