How AI Happens Data Scientist & Developer Advocate Kristen Kehrer
Kristen is also the founder of Data Moves Me, a company that offers courses, live training, and career development. She hosts The Cool Data Projects Show, where she interviews AI, machine learning (ML), and deep learning (DL) experts about their projects. Points From This Episode:
- Kristen’s background in the data science world and what led her to her role at Comet.
- What it means to be a developer advocate and build community.
- Some of the coolest AI, ML, and DL ideas from The Cool Data Projects Show!
- One of the computer vision projects Kristen is working on that uses Kaggle datasets.
- How Roboflow can help you deploy a computer vision model in an afternoon.
- The amount of data that is actually needed for object detection.
- Solving the challenge of contextualization for computer vision models.
- A look at attention mechanisms in explainable AI and how to tackle large datasets.
- Insight into the motivations behind Kristen’s school bus project.
- The value of learning through building and solving “real” problems.
- How Kristen’s background as a data scientist lends itself to computer vision.
- Free and easily-available resources that others in the space have created to assist you.
- Advice for those forging their own careers: get involved in the community!
Tweetables:
“I’m finding people who are working on really cool things and focusing on the methodology and approach. I want to know: how did you collect your data? What algorithm are you using? What algorithms did you consider? What were the challenges that you faced?” — @DataMovesHer [0:05:55]
“A lot of times, it comes back to [the fact that] more data is always better!” — @DataMovesHer [0:15:40]
“I like [to do computer vision] projects that allow me to solve a problem that is actually going on in my life. When I do one, suddenly, it becomes a lot easier to see other ways that I can make other parts of my life easier.” — @DataMovesHer [0:18:59]
“The best thing you can do is to get involved in the community. It doesn’t matter whether that community is on Reddit, Slack, or LinkedIn.” — @DataMovesHer [0:23:32]
Links Mentioned in Today’s Episode: