The Urban Dictionary of data science meetups

Meetings are a good way to meet fellow data scientists and get feedback on your results. You can also join some meetups run by academic institutions or business schools to learn more about data science and its applications.

I’m sure many of you already know about data science meetups run by various groups around the country, but I’m going to do a mini-rant to say that I’m not a data scientist and I don’t have any ideas on how I would run a meetup.

I am a data scientist, I have a lot of ideas, but I really don’t know why I’m doing this meetup. I just do it to meet people and get feedback. I know that there are many data science meetups out there and that there are many people who are more creative than me, but I think that’s normal. I’m just doing a hobby that I enjoy, and I dont have any ulterior motives, and I hope its nothing nefarious.

In some ways, there are worse people in the world than data scientists. A lot of people think that data science is all about numbers and statistics, and thats bullshit. It’s not. Data science is about creating models that are interpretable, and models that can be used to model other human behaviors or to predict other human behaviors. If you know how to do that, you can use your data science know-how to solve problems that require a higher level of thinking.

This is all well and good, but what if none of my data science know-how can solve your problem? What if you are a data scientist trying to make sense of your data and create models that you can use to predict the behavior of other people with your data? What if that someone is also a data scientist? That’s a problem, and that’s a problem for you and your data scientists.

The problem is that data scientists are not always people who can make sense of data. A lot of the time I’m with my data scientist and she’s also a really good programmer. In situations like this, we forget that our data scientists have to be smart and knowledgeable about data analysis. This is why I like to describe data scientists as “statisticians” or “people who know how to do data analysis.

I think data scientists are in a strange position when it comes to statistics. In order to do good data analysis, you have to know statistics, because you have to know a lot to do good data analysis. So I think it’s a bit of a catch-22. At the same time, statistics are a wonderful way to explain and interpret complex data.

So when I think of data scientists, I think of people who might like to get in a lot of trouble or work for big companies who have to justify their existence. But since data science is so new, I don’t know any data scientists from a PR or marketing perspective; I know of them from academics and from other researchers who are doing data science.

If you’re a data scientist you are probably more of a statistician than a programmer, or at least you have to get into those shoes. But the good news is that data science is a field with a lot of opportunities for people with diverse backgrounds, who are interested in a wide variety of topics.

Wow! I can't believe we finally got to meet in person. You probably remember me from class or an event, and that's why this profile is so interesting - it traces my journey from student-athlete at the University of California Davis into a successful entrepreneur with multiple ventures under her belt by age 25

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