Participatory Python 2 - Machine Learning

Our second participatory python session will be focused on machine learning!

According to wikipedia, Machine learning is a scientific discipline that is concerned with the design and development of algorithms that allow computers to evolve behaviors based on empirical data, such as from sensor data or databases. A learner can take advantage of examples (data) to capture characteristics of interest of their unknown underlying probability distribution. Data can be seen as examples that illustrate relations between observed variables. A major focus of machine learning research is to automatically learn to recognize complex patterns and make intelligent decisions based on data; the difficulty lies in the fact that the set of all possible behaviors given all possible inputs is too large to be covered by the set of observed examples (training data). Hence the learner must generalize from the given examples, so as to be able to produce a useful output in new cases.

The goal of participatory python is to get people who are already involved in a particular field and are using python in that field a chance to meet each other and discuss how they're using those tools. The size of the meeting is kept small so that everyone there can present and thus hopefully show something interesting and useful to the other attendees. (The smallness has other benefits, like allowing us to host the meeting in smaller spaces).

The format of participatory python is as follows: up to 10 people attend and present short (up to 5 minute) presentations on the topic (Machine Learning). Doors will open early to start off with conversation and afterward some of us will head to a bar to keep the conversation going! Looking forward to seeing you there!