Prof Sheldon H. Jacobson will be giving a talk on “Bits and Bytes on March Madness” about his research in probabilistic analysis in NCAA basketball tournament. See you there!
Where: Transportation Building 303
When: 5pm, March 12 (Monday)
Join us for our second Python Workshop on Tuesday, Feb 20th at 6 pm. This workshop will focus on data visualization using Pandas and Matplotlib. The basic idea is to analyze and visualize some interesting datasets from either Kaggle or a popular lab course. Bring your laptops and code along!
We’re also holding our elections for this year’s executive team right after the workshop. If you can join us to vote on the new team, that would be greatly appreciated.
If you have any questions, you can reach us at informs.illinois@gmail.com.
Where: TB 303
When: Tuesday, Feb 20th at 6pm.
We will be opening this semester with a kick-off event on Thursday (1/25) at 5pm. Prof Richard Sowers will be joining us for an interesting talk on Operations Research and INFORMS. We will discuss events planned this semester (seminars, corporate info sessions, student talks, social events, etc) and ways in which you can get involved. If you are interested in joining the organizing team, this is the perfect time, as we will also discuss elections for this year’s execute team.
Free pizza will be served. Looking forward to see you!
Where: Tb 303
When: Thursday (1/25) 5pm
If you are an undergrad student and looking to improve or show off your data science skills, come join us on Thursday night.
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Our chapter will be kicking off the Principal Challenge in Analytics Innovation – a national data science competition for undergraduate students. We will explain the competition, give an overview of the data, and answer any questions. Data science is a team sport! You can form a team on your own or let us know you are looking and we can help!
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Where: Transportation Building 303
When: Thursday, November 9th at 6pm
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Comment below or email us questions at informs.illinois@gmail.com. See you there!
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Learn more or register at https://www.ideaconnection.com/principal-challenge/
Twitter: https://twitter.com/INFORMS_UIUC
INFORMS will be holding an introductory tutorial session for k-Means Clustering!
Professor Carolyn Beck of the ISE department will be joining us to give a 30 minute seminar on k-means clustering, including an overview of its strengths and weaknesses, implementation, and Lloyd’s algorithm. Following a Q&A with Professor Beck, we will also be providing a tutorial on implementing the k-means algorithm on the famous Iris Flower data set. The tutorial will take place in Python, using Jupyter Notebook. It will be beneficial to bring your laptops but installing Jupyter is not required.
Where: TB 303
When: Wednesday 10/11 5:30pm
Guest Speaker: Professor Carolyn Beck, Ph.D.
About k-means
k-means clustering is a standard tool in data analysis of numerical features, used to classify unlabeled data quickly. It is a heuristic but highly effective method used both in industry and academia based on the location of a k n-dimensional centroids. The k-means algorithm is both simple and intuitive, and forms the basis on which many more sophisticated methods of clustering are built. It finds use cases in cyber security classifying potentially malicious data, in online retail classifying customer types to determine what items to show, and in campaign-planning to identify what opinions voters hold on multiple, dependent issues.
Twitter: https://twitter.com/INFORMS_UIUC
INFORMS will be holding an introductory tutorial session for Python!
Python is an interpreted, open-sourced, and continuously evolving programming language for general purposes. In light of several popular packages (or libraries), it becomes almost an omnipotent environment for modeling, data analytics, scientific computing, etc.
We will be using Jupyter notebook for the tutorial purposes. It will be beneficial if you bring your laptops but installing Jupyter is not required.
In this tutorial, we will cover:
- Data types (Numbers, Strings, Booleans)
- Containers (Lists, Tuples, Dictionaries)
- Classes
- Functions
- Conditionals and loops
- Reading/writing CSV files
- Introduction to packages (NumPy, SciPy, Pandas, Matplotlib)
- Some demos
What’s next? Join us for some delicious food and happy time at Murphy’s!
Where: TB 303
When: Thursday 9/28 5pm
Twitter: https://twitter.com/INFORMS_UIUC
INFORMS at the University of Illinois at Urbana-Champaign 