Portland Data Science Group

How do you get the most out of data that's expensive to collect? That's a common problem faced by businesses and government agencies like the US Energy Information Administration, who have worked to quantify in detail the factors influencing electricity and natural gas usage by households across the US. For November and December, we'll be exploring the EIA's Residential Energy Consumption Survey, and considering how we would communicate our findings to a non-data-scientist stakeholder, such as a city planner or a housing developer. Everyone from beginners to experts is welcome. If you miss a session, we can put you into an existing group and get you up to speed. As always, our three objectives are: 1. Provide skill-level-appropriate challenges to all participants. 2. Participants collaborate with and learn from one another. 3. Those who attend all four Sundays finish a project they can add to their github/resume/portfolio. Bring your laptop and your favorite data analysis software! We're language-agnostic. If you don't already have a favorite analysis tool, most of our beginners start with anaconda via the instructions here: http://goo.gl/W8Q6cV

How do you get the most out of data that's expensive to collect? That's a common problem faced by businesses and government agencies like the US Energy Information Administration, who have worked to quantify in detail the factors influencing electricity and natural gas usage by households across the US. For November and December, we'll be exploring the EIA's Residential Energy Consumption Survey, and considering how we would communicate our findings to a non-data-scientist stakeholder, such as a city planner or a housing developer. Everyone from beginners to experts is welcome. If you miss a session, we can put you into an existing group and get you up to speed. As always, our three objectives are: 1. Provide skill-level-appropriate challenges to all participants. 2. Participants collaborate with and learn from one another. 3. Those who attend all four Sundays finish a project they can add to their github/resume/portfolio. Bring your laptop and your favorite data analysis software! We're language-agnostic. If you don't already have a favorite analysis tool, most of our beginners start with anaconda via the instructions here: http://goo.gl/W8Q6cV

How do you get the most out of data that's expensive to collect? That's a common problem faced by businesses and government agencies like the US Energy Information Administration, who have worked to quantify in detail the factors influencing electricity and natural gas usage by households across the US. For November and December, we'll be exploring the EIA's Residential Energy Consumption Survey, and considering how we would communicate our findings to a non-data-scientist stakeholder, such as a city planner or a housing developer. Everyone from beginners to experts is welcome. If you miss a session, we can put you into an existing group and get you up to speed. As always, our three objectives are: 1. Provide skill-level-appropriate challenges to all participants. 2. Participants collaborate with and learn from one another. 3. Those who attend all four Sundays finish a project they can add to their github/resume/portfolio. Bring your laptop and your favorite data analysis software! We're language-agnostic. If you don't already have a favorite analysis tool, most of our beginners start with anaconda via the instructions here: http://goo.gl/W8Q6cV

We've got some amazing folk in our group and that can lead to some great talks. However, it's hard for the presenters to know if a subject will be interesting to the group. Let's help them out and suggest topics. What talks would you be interested in attending or giving? Please use the comments to request a talk, volunteer for a talk, or provide feedback on someone else's suggestion.