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May 11, 2012
Galois Tech Talk: An Analysis of Analysis
Galois, Inc

Presented by Charles Parker

A basic problem in computer science is binary classification, in which an algorithm applies a binary label to data based on the presence or absence of some phenomenon. Problems of this type abound in areas as diverse as computational biology, multimedia indexing, and anomaly detection. Evaluating the performance of a binary labeling algorithm is itself a complex task, often based on a domain-dependent notion of the relative cost of "false positives" versus "false negatives". As these costs are often not available to researchers or engineers, a number of methods are used to provide a cost-independent analysis of performance. In this talk, I will examine a number of these methods both theoretically and experimentally. The presented results suggest a set of best practices for evaluating binary classification algorithms, while questioning whether a cost-independent analysis is even possible.

Mar 12, 2013
Galois Tech Talk: Inferring Phylogenies Using Evolutionary Algorithms
Galois, Inc

Presented by Erlend Hamberg.

An important problem in genetics is phylogenetic inference: Coming up with good hypotheses for the evolutionary relationship between species – usually represented as a “family tree”. As the amount of molecular data (e.g. DNA sequences) quickly grows, efficient algorithms become increasingly important to analyze this data. A maximum-likelihood approach with models for nucleotide evolution allows us to use all the sequence data, but is a computationally expensive approach. The number of possible trees also grows rapidly as we include more species. It is therefore necessary to use heuristic search methods to find good hypotheses for the “true” tree. Evolutionary algorithms (EA) is a class of such search/optimization algorithms that has been shown to perform well in other areas where the search space is large and irregular. I will explain my approach and my findings from using an evolutionary algorithm for inferring phylogenies from molecular data.

Jun 5, 2013
PyLadies PDX presents: Algorithms as Recipes for Computer Programming
In Other Words Feminist Community Center

Join us for Algorithms as Recipes for Computer Programming, presented by Rebekah Golden, a local developer at JanRain.

Algorithms sometimes intimidate but really they are just recipes for computers to follow to do repetitive tasks. This is a beginner class on recognizing when an algorithm would be useful, basic methods for creating one in Python, and a quick look at algorithms that have been written by others for common tasks. Presentation is in a room without computers but if you bring yours you can build a computer recipe or two yourself. Discussion and repetitive task descriptions welcome.

This meeting is open to the public. People of all genders are welcome to attend.

Oct 27, 2015
PDX PHP - Demystifying TDD & 5 Algorithms Every Web Developer Can Use and Understand

Join us for an evening of two talks at MotoSport!

John Kelly will give a hands on talk on demystifying Test-Driven Development (TDD). We're going to go through a real example that isn't the "easy" example you'll find in books. We'll go over why, as well as how to implement TDD in your development workflow.


Sheldon Kreger will share "5 Algorithms Every Web Developer Can Use and Understand." Although we don't often implement algorithms in our work, there are several of them which can prove to be useful in our applications. Content recommendations, search engines, and natural language processing are just a few examples of algorithms leveraged online. Sheldon will describe the basic mathematics behind the scenes, and show some demonstrations using the Algorithmia API ( to access advanced algorithms from within PHP applications, including Wordpress and Drupal.

Food and drink will be provided.

Thanks to MotoSport for hosting this month's meeting!

Feb 9
CANCELED WEATHER: Time Series Prediction of SNOTEL Data
Portland Community Church

Check back for a rescheduled time.

Sunil Rao will be presenting his past research on SNOTEL data using the time series prediction.

Drought is a serious problem in much of the U.S., with the worst conditions across the southern and western parts of the nation. Much of irrigation and recreation facilities depend on proper forecasting of streamflow. The water supply for irrigation largely comes from rivers and creeks, whose streamflow originates from the springtime melting of winter snow. A water supply forecast is a prediction of streamflow volume that will flow past a point on a stream during a specified season, typically in the spring and summer. One of the primary sources for the data is through NRCS SNOTEL( Snow Telemetry) data (available to public as part of tax dollars at work). In this demo, we showcase one such tool (Timeseries ARIMAX model) to forecast Streamflow volume for Deschutes River Basin, OR and later compare with actual data to see how it performed.

If you would like to join the discussion check us out on Zoom

Do you want to learn and share your passion in a supportive community? Knowledge Mavens is an ethos of sharing, creativity, and inspiration.

Our Meetup provides an opportunity to "Show and Tell" followed by feedback and Q&A. You'll have the opportunity to share with our channels such as Meetup, GitHub, YouTube, and Facebook to connect with more passionate people.

The second half of our session we'll collaborate on new topics. The winner wins an award for the most interesting topic and the opportunity to share in an upcoming session.