SDS 157: The Amazing World of a Data Science Meetup

SDS 157: The Amazing World of a Data Science Meetup

Podcast Data Science Meetup

Welcome to episode #157 of the Super Data Science Podcast. Here we go!

Admit it… we spend most of the time sitting and working in front of our monitors. No doubt, the hard work is indeed admirable! But, meeting people within and outside your field is also important in maneuvering your career. Our guest for today’s episode, Mary Loubele, is going to discuss the importance of organizing and attending meetups for data scientists.

Subscribe on iTunesStitcher Radio or TuneIn

About Mary Loubele

Mary Loubele is a Senior Data Engineer at TalkIQ, an organization based in Kitchener, Canada. Her focus during her graduate studies was on medical image computing. Her career mostly revolved around data science and engineering. She is the organizer of a group in meetup.com that mostly consists of experts and enthusiasts from the math, computer science, and programming field.

Overview

On today’s Super Data Science Podcast episode, I will be talking to Mary Loubele from Canada. I met her through few of my courses. Though already an established data scientist, she says that taking these courses help her refresh her memory and learn new things.

Listen as she shares her extensive knowledge of planning and organizing meetups. First off, Mary shares her journey and how it led her to data science. Her interests revolve around machine learning, deep learning, NLP, and engineering. But, how did deep learning and NLP changed and grown after five years? Mary answers and gives insights on the difficulties and the influences among the fields.

If you think you have been jumping from one industry to a completely different industry and feels that it won’t help you advance your career as a data scientist, then you should hear the advice of Mary. Mary has been providing her service as a data scientist in different industries – marketing, sales, customer service, IT support and research. The one thing she loves about the broadness of her career is the benefit of networking with people. Seeing the tools evolving is also one of the reasons.

Her passion for organizing meetups started when she got inspired by the conference she attended. She started a group called Interactions KW on meetup.com. But, how different are these meetups from the meetups you might’ve attended to? These are technical meetups. Her group, for example, holds a hands-on station for data scientists. This is to help them try out something they won’t ever try alone when learning.

You should not miss the tips Mary gave for organizing meetups. She discusses the following:

  • Finding a place.
  • Recruiting members.
  • Getting sponsors.
  • Encouraging people to communicate with each other.

First-timers should not be afraid to attend meetups. Actively participate and be proactive! This could help you meet people to advance your career. You learn and share experiences with them. If you’re having a hard time getting to your goals, maybe they could help you solve the complications or advice you about it.

There are so many things that you could get from meetups – not only for your career but also for your wellbeing. So, listen to Mary Loubele as she discusses more on this episode!

In this episode you will learn:

  • Mary Loubele shares what’s happening in her career and what’s busying her right now. (04:30)
  • Mary’s take on the future of deep learning and NLP. (09:27)
  • How does it feel to constantly shift different industries for your data science skills? (14:48)
  • Organizing meetups is a hobby of Marie Loubele that grew and gained following. (15:49)
  • Data scientists can greatly benefit from technical meetups (especially with hands-on stations.) (17:34)
  • Tips on organizing your first meetup. (22:25)
  • How do you encourage people to interact with each other? (27:20)
  • From her experience, Mary tells her biggest accomplishment she’s achieved through the meetups. (30:12)
  • Attending meetups can help you grow your career. (33:06)

Items mentioned in this podcast:

Follow Mary

Episode Transcript

0

Full Podcast Transcript

Expand to view full transcript

Kirill Eremenko: This is Episode Number 157 with Data Science Meetup organizer and enthusiast, Mary Loubele.
Welcome to the Super Data Science Podcast. My name is Kirill Eremenko, Data Science Coach and Lifestyle Entrepreneur. Each week we bring you inspiring people and ideas to help you build your successful career in data science. Thanks for being here today, and now let's make the complex, simple.

Hello, and welcome back to this Super Data Science Podcast. It's a very exciting time to be onboard today. Today I had a chat with Mary Loubele, who is one of our students in our courses. She's taken the Data Science A to Z course, and now she's looking into a Deep Learning A to Z course as well, and it's a very interesting story for two reasons.

First of all, because Mary is taking our courses, but she is actually already a data scientist. So, I was interested to learn about that ... that somebody who's already has a career in data science, they're taking the courses to further their studies, or refresh certain things, learn new bits and pieces, and fill in those gaps that might exist in their knowledge, which is a very admirable thing to do. The second reason why this podcast can be useful to you is because we talked about meetups. Mary has quite extensive knowledge in meetups. Starting from the second half of this podcast, we were focusing on her experience in this space.

So, not only does she attend meetups, but she's actually now started organizing them, and she's had quite a bit of success in that space. She knows how to put a meetup together, how to get people to come, how to get that location. And even, she had some good accomplishments in the space for meetups for which she actually was able to attend a conference in San Francisco, and she'll talk a bit more about that. So, if you ever intend on creating a meetup, organizing a meetup yourself, or if you're kind of wondering whether or not you should attend a data science meetup, you can get some valuable insights from Mary in today's episode.

On that note, let's dive straight into it. Without further ado, I bring to you, Mary Loubele.
Welcome ladies and gentlemen to this Super Data Science Podcast. Very excited to have you onboard. Today we have Mary Loubele calling in from Canada. Mary, welcome to the show. How are you doing?

Mary Loubele: Good. How are you?

Kirill Eremenko: I'm very good as well. Just before the show, you mentioned that it was a snow storm in that part of Canada where you are, and you couldn't get out of your house for three days? What's going on with this weather? How are you holding up right now?

Mary Loubele: I know, it's like a crazy winter this year. On Saturday morning ice rain started and it has been raining since yesterday evening, and it still took a while 'til all the ice was gone that we could go out safely.

Kirill Eremenko: Wow. I just had this thought of somebody listening to this podcast. I don't know, somewhere in a tropical country ... where it's blazing hot and maybe there's never been ice rain there before. It's like ... what is ice rain? Is it like ice falling from the sky, type of hail, like that?

Mary Loubele: Actually it is like frozen rain that is falling from the sky. But, what you also see on the tree branches actually is that the ice stays on it. So, you actually have ... It's a weird thing. And what we now have, we had like three or four centimeters of ice just on the roads.

Kirill Eremenko: Yeah, wow. That's crazy. Okay, well, at least, as you mentioned also before, in data science you can work from home. In your role, you were able to do that. That makes things a little bit easier, doesn't it?

Mary Loubele: Yeah, that's true.

Kirill Eremenko: Okay, all right. Well, fantastic to have you on the show. You have a very interesting background and you're one of our students. Can you tell us in which courses you've participated of Super Data Science?

Mary Loubele: I have done the A to Z Data Science, and I've also looked at the Deep Learning Data Science course.

Kirill Eremenko: Okay, and is that how you got started into data science? Or did you do that course already after you were a data scientist?

Mary Loubele: I did those courses already, after that I was in data science. So, what I mostly do with these ones is like ... having them either as a refresher or otherwise for learning new things.

Kirill Eremenko: Okay, and what did you think? Were they useful? Did they live up to your expectations?

Mary Loubele: Yeah, indeed, they are really useful. For example, the part what I really loved a lot was where you're talking about the model maintenance.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: So the different strategies from, saying when you should be retraining your model, or in which cases you actually should be looking at a better model. That's a part I really loved a lot about it. Also, for deep learning, I liked the part where you are explaining everything. You also say, these are the libraries that you used to set everything up. So, it's really interesting and nice.

Kirill Eremenko: Yeah.

Mary Loubele: And finally the part I also loved a lot, is where you are giving suggestions about how you need to do presentations about data science. How you need to deal with the less technical audience, so ... it's awesome.

Kirill Eremenko: Yeah. Okay, thank you. Interestingly, I was just actually ... somehow got to that course yesterday, to the Data Science A to Z, and I was looking exactly at that part about statistics. I think it was the case that I needed a refresher myself. So, I went into the course, and I actually checked out some videos. And it was so, in a way so weird, because it was ... Back then I didn't have the beard, and also I sounded a bit different. So, it was quite strange listening to myself. Yeah, it brings up interesting memories from back then.

Mary Loubele: Yeah. I can believe so.

Kirill Eremenko: All right, well, thank you so much for coming on the show. It's going to be quite an interesting chat, because on one hand you are studying the courses, but on the other hand, as you mentioned, you already have a career in data science. And you're progressing through that, and also you are very active in your career.

You're also helping others. You're arranging meetups in Canada about engineering and data science, and technical aspects, so that will be quite an interesting chat.
Maybe to kick us off, tell us a bit about your career. How did you get into the space of data science in the first place?

Mary Loubele: When I was studying, I studied engineering with a focus on numerical simulations.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Then when I graduated, I started a PhD in Medical Image Computing. Then actually, the subject that I was doing was automatically evaluating the image quality of 3D images for dentists. How the dentist normally would do that, they would put points on a skull. Then they would measure those points with a caliper. Then they would be scanning the object, then measuring it on the radiographs, then evaluating the differences, and see how accurate actually those radiographs were.

The challenge with that is they only could write down or do seven or eight measurements. It's like really heavy. There I actually worked on ... I would build a model with a laser scanner, and then I would compare the measurements that I had from my laser scanner. I would compare them with 3D images from one of the scans. That way you actually would have a data pipeline that you were building. And at the end of the whole process, you could say this scanner is so accurate and that other scanner is so accurate. That was actually the first part what you could say was some kind of data science road that I was on.

Kirill Eremenko: All right, so that's quite an interesting application of data science. And where did that take you from there?

Mary Loubele: Next, I was a year of post-doc in Belgium. Eventually, I moved to Canada, and there my first job in the industry was at Maluuba. And Maluuba was back then building a Siri clone, which would mean that I was actually working as an NLP Software Developer.

Kirill Eremenko: Okay, very cool. So, is that deep NLP or ... like no deep learning NLP?

Mary Loubele: No, it was no deep learning NLP, because it was like in 2012/2013. Back then, I was more like training machine learning models with SPMs more, also a combination of text mining. So a combination of right axis and building [inaudible 00:09:15] and everything, Next, I also was working on NER for driving all the different objects and different entities that you have from [inaudible 00:09:30].

Kirill Eremenko: Okay, okay gotcha. What do you think of how NLP has changed over the years? You know, given that you've looked at our Deep Learning Course, well actually not in the Deep Learning Course; we just talk about Deep learning there. We have a separate course on NLP, Deep Learning and NLP. But maybe you've come across Deep Learning and NLP together.

What would your comments be on how it's changed since those days when you worked on it? Is it drastically different now, or has it not grown that much in the past ... what is it, five years?

Mary Loubele: The main difference is actually when I heavily was involved in the part from the NLP, the future engineering was much more important, so that you need to make sure that you have all the different list of [inaudible 00:10:18] and also making sure that you have clean data. Where now the focus with Deep Learning is much more now. I'm having larger sets of data and then actually making sure that the algorithm itself will actually find the features.

From that point of view, it's actually harder to find correct parameters for the Deep Learning algorithm, because you have less influence on it yourself. Whether you're doing the future engineering, you can look more like - Where are the gaps that I had? Then you can just feed it in extra information.

Kirill Eremenko: Okay, so yeah, different approach. I think I also kind of ... learned a bit about that. I actually encountered that first when I was doing learning about computer vision, computer vision before it was finding those features and doing the [inaudible 00:11:15] and understanding what features to identify. Whereas now it's a bit different. Right now it's more ... you're right. The Deep Learning algorithm is supposed to find those features on its own. So yeah, Deep Learning is revolutionizing everything by the sounds of it.

Mary Loubele: Yeah, that's true.

Kirill Eremenko: Okay, alright, so you worked on NLP for some time, and then where did you move onto from there?

Mary Loubele: So then I moved to Desire to Learn, which was a company that is building online learning solutions. There I was initially part of the Predictive Analytics team, and one of my jobs there was evaluating the predictive algorithms for the students. There were two types of algorithms. One was trying to predict how well a student was going to do in a course. The second product that we had was actually trying to recommend courses for students and giving the courses that would make sure that the students would graduate in a fastest possible time.

Kirill Eremenko: Oh, okay.

Mary Loubele: Yeah. So my goal there was like ... For example, when we would install a recommendation system with a new school, then I needed to say how accurate the algorithm would be for that school itself. It's always important when the school buys such a product that they also know that it will actually perform well on their students as well.

Kirill Eremenko: Okay, gotcha. And then where did you move on from there? You had a role at Funnel Cake and now you're at Talk IQ. Tell us a bit about those.

Mary Loubele: At Funnel Cake ... that was a really small startup. I was one of the first employees. There, we were working on a combination of sales and marketing analytics, so from sales, I know that ... for example ... we got data from SalesForce, a hub spot. Then, for the marketing analytics, we had data from, for an example, Marketo, or hub spots.

The goal there was going back to model, for example - which ages of a website are you looking at; which part of your sales funnel? That way the marketing people can actually tailor the message better to their leads.

Kirill Eremenko: Okay, gotcha. So, marketing, and in Talk IQ?

Mary Loubele: Talk I.Q.? There we automatically transcribed sales and customer support calls, and then we were mathematically deriving - Where is the customer happy? Where are they complaining about a price? Where are they saying they want to buy the product?

Kirill Eremenko: Yeap.

Mary Loubele: And automatically give all those moments to the client. Then one of the big projects I am next working on is ranking this sales course to see which sales calls have a lot of potential, and should lead into a sale, and which of the sales calls will have less potential, and you should better leave those clients alone for now.

Kirill Eremenko: Mmm.

Mary Loubele: Because they currently don't need the product.

Kirill Eremenko: Okay. Very interesting. You've applied data science in so many different industries, from science and ... research, to natural language processing ... to education, to marketing, to now, sales. This is very interesting journey.
How does it feel, constantly changing your either industry or area in which you are applying data science? Is that exciting, or does it come with some, sort of ... is it difficult to do that all the time?

Mary Loubele: It's actually exciting, because the benefit from that way is ideas that you have learned in one industry, you can actually transfer that to another industry.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: That way things keep exciting and are not really getting boring.
Also, the nice thing is that you also see tools evolving, and you see different methods involving, which is really exciting. It also allows you to work with different types of people, which allows you to grow your network, which is also fun.

Kirill Eremenko: Fantastic.
Speaking of networks. You're very passionate about meetup groups. Let's talk about that. How did this hobby start, that you're arranging meetup groups in your area?

Mary Loubele: Myself, originally, I went to Adult Net User group. Then, one of the user groups I loved the most is where there was a hands-on session where you could play with technology yourself.

Kirill Eremenko: Yeap.

Mary Loubele: Then, eventually, I started going to KW-Intersections the first time. They had meetup session about quantum computing. The next time I went to the session, the organizer moved to Germany, so he couldn't keep organizing the meetup anymore, so because no one else was interested in taking over the group, I actually took over the group and started building the group since then.

When I took over the group, we had one hundred twenty members. That was two-and-a-half years ago, and now we are reaching almost six hundred members.

Kirill Eremenko: Wow. Wow. How many people attend the meetups?

Mary Loubele: It depends a bit. It's around twenty-five to thirty people. Sometimes when you have bigger ones, you can go to forty to forty-five people.

Kirill Eremenko: Okay, wow. How often are these meetups?

Mary Loubele: KW-Intersections is monthly, each second Tuesday of the month.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Last November, I took over the [inaudible 00:17:16] Science Meetup. Since then, we are also meeting monthly. Once in a while, I'm also helping out with the [inaudible 00:17:24] Meetup. Also, I'm active in the Women in Tech Meetup group.

Kirill Eremenko: All right. Let's talk more about the benefits of Meetups. What are the benefits of going to a Meetup? What would you say ... to our listeners who have never been to a technical Meetup? What's the use and what value will they get from going to a technical Meetup?

Mary Loubele: I would say ... it's like if your studying alone ... at home. You always have the feeling like you are not progressing well.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: It's also kind of depressing. Well, if you go to a technical meetup where people are passionate about the same things, then you can see what your strengths and what your weaknesses are. Then you sometimes might see that you have more knowledge about certain topics than other people, which in a way also makes you feel good.
Second thing is also that you're just learning things together, that you meet new people, which is also exciting.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Because also it sometimes might be challenging for meeting new people, because it's scary for everyone, but you just go a lot of times to meetups. You're less scared of it, and you also feel more confident.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Also, for example, it's also a way to connect with extra women in your region, or just to grow your network.

Kirill Eremenko: Yeah. That's cool. I also wanted to comment on that. For me ... generally meetups are quite useful, not just technical, but even what you pointed out ... sitting at home alone all the time ... and working or studying, can be... you feel like you're missing out, that life is flying by sometimes. But getting out there and meeting other people and learning about their stories, and socializing in person, not just over the internet, can be very useful. Especially, if you can combine it with something that you love. A technical meetup on a topic that you are studying, such a data science, because you'll definitely find like-minded people, and you'll have things to talk about.

So, that's the first part, about meetups. What about hands-on sessions? In the first part of this broadcast, you mentioned that you have a really cool story about why hands-on sessions at technical meetups are important.
Can you tell us a bit more about that? Why do you think hands-on sessions are important? Also, what's the cool story?

Mary Loubele: If you're trying something out at home alone, certainly with something technical, it might get frustrating if things don't work out.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: If you, for example, if you are working together at a hands-on session, then you actually know what the struggles might be, and someone else might be able to help you out, which will help you go to the end of the session. You'll have accomplished something. You feel happy, and that way you will be able to work further on it at home. You feel more confident than if you just would have worked on it at home; you maybe just would have given up about it.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: An exciting story that I have there is ... I work together with the Elasticsearch Meetup a few months ago, where I built in hands-on sessions. What I built there was building a [inaudible 00:20:52] dashboard. It was really starting from the API ... so getting your [inaudible 00:20:59]data, [inaudible 00:20:59]an Elasticsearch, built a dashboard. I also built a sentiment analyzer, and I made sure that all the information that people needed was on a USB key, so that everybody could install it.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Everybody could learn how to work with Elasticsearch. There, I also had a friend, that now works at Elasticsearch. She told me about the Elasticon Conference, and she said she could get me free tickets for the conference.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Also, because of other women in tech, I got the minority band for a free plane ticket and actually organizing a Meetup in Canada gave me like a free ticket for Elasticon conference in San Francisco, which allowed me to visit San Francisco for the first time in my life.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Which was kind of exciting.

Kirill Eremenko: Mm-hmm (affirmative). Nice, nice. Congratulations. That's really cool. Did you enjoy the conference?

Speaker 3: Yeah. It was really nice. My friends and I were leading their Birds of a Feather session about using a LP with Elasticsearch, and we had the session at the conference which had the most attendees, which was kind of cool.

Kirill Eremenko: Wow. That's so cool. Congrats. That's awesome. Sounds really cool.
So, not only in the meetups, but expanding other places as well.

Speaker 3: Yeah. That's true.

Kirill Eremenko: Yeah. Fantastic. Okay. That's exciting.

What else can you tell us about ... what else ... Organizing the meetups, is it difficult to organize? What are some tricks. Let's say somebody wants to start a meetup. By the way, one of our students, who I met at [inaudible 00:22:39] last year ... the first thing he did ... Rico [inaudible 00:22:43], he was also the focus. The first thing he did when he got back to Germany, he started a meetup.

I'm seeing this more and more. People are more proactive in the data science community and starting meetups. We have [inaudible 00:22:55], who had talked about meetups as well. A lot more people are getting into the space.
Let's say somebody lives in a city where there isn't a data science meetup group, and they want to get started. What would your recommendations for organizing one of these be?

Mary Loubele: The big challenge, what you always have first, is finding a place where you can host a meetup. I suggest there, for example, that you would ask your company, or a company of a friend, whether they would provide a small meeting room where you can organize your meetup.

Kirill Eremenko: Yeap.

Mary Loubele: The second challenge is also indeed getting members first in your meetup group.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: That's like a challenging part if you're organizing something for the first time. Will there actually be people showing up?

Kirill Eremenko: Yeah. Yeah. I think you shouldn't be discouraged if people don't show up, or if one person shows up. It's totally fine at the start, right? It's about the consistency. If you do it consistently, and you have something to share, people will come ... eventually. Don't expect it right away.

Mary Loubele: Yeah, no, it's true. When I took over KW-Intersections, we had one meeting, and we only like eleven people which is kind of low, but then you just get a little worried. But, right now, we have grown like ... Yes, we've had sessions with thirty people. I have sessions of forty people, and then you're now worried that your room is actually going to be too small for once.

Kirill Eremenko: The opposite problem.

Mary Loubele: Yeah. It's true. But, also what is important when you're starting a meetup, is making sure you have a plan for the first three sessions.

Kirill Eremenko: Yeah. Okay. Okay. That's a good tip. Why is that important?

Mary Loubele: It's easier to start a habit when you have done something three times than when you have only done something one or two times. It also is important that people will get to know you, get to know the meetup. It's not always that people will start to step up right at the first meeting or second meeting ... that they will say, "Yeah, I'm definitely interesting in speaking the next time."

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: That's a tough thing, so just make sure you have like a plan for three meetings.

Kirill Eremenko: Okay. Okay. So, so far, we have those three tips. Hope you guys are writing this down, because those who are planning on having meetups, or want to give it a go ...

First of all, figure out the space, where you're gonna have it. Talk to maybe your company, or local communities that can maybe provide you a room, because it's important. If you want to meet up, you have to have place to meet up. Or, maybe you can go to some restaurant on a non-busy night or something like that.
Then, don't be discouraged if you have low attendees on the first go. That's okay. That happens. Also, have at least three meeting plans in mind when you start off, to form that habit, to keep you going.
Anything else? Anything other tips you can share?

Mary Loubele: Also, it sometimes might help, but then you also need a sponsor, is having some stuff or having some drinks, which also indeed makes it a bit more enjoyable.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Also, for example, if you are focusing on a more technical topic, you might have more introvert people who are showing up. Don't try to have a real happy networking part in the beginning, because it actually might scare off some people in the beginning.

Kirill Eremenko: Interesting. It kind of reminds me of what's happened at our ... in contrast with what happened Data Science Go last year in San Diego in 2017 ... we were expecting that it will be quite a challenge to get people to socialize with each other, to ... you know, participate in communications and things like that. Kind of like the same in which you just described. In technical topics, a lot of time there's more introverted people, therefore, it's harder to get conversations going.

But what we found to our surprise, even before the conference started, when people were just waiting and they just got their badges, and they're waiting in the lobby to proceed inside the room, everybody was talking to each other. They were having great time, and they were already making connections and so on. Somehow, it just magically happened.

I don't know. Maybe it was just like a lucky experience for us. Did you ever have a similar situation or ... do you usually need to put in quite bit of effort to encourage people to communicate with each other?

Mary Loubele: Actually, most of the times it's fine. What I also see is people not starting immediately from the beginning, but at the end they just keep talking.

Kirill Eremenko: Yeah. True. Once they get going, it's hard to stop.

Mary Loubele: It's just sometimes I have noticed ones, at the Women in Tech session, is if there are a lot of people there for the first time.

Kirill Eremenko: Yeah?

Mary Loubele: I see that they're kind of nervous and just sitting there and looking at each other. I was just going around the room ... to say, hello, to everyone.

Kirill Eremenko: Yeah.

Mary Loubele: Asking where they were from. That also breaks the ice.

Kirill Eremenko: Yeah. Definitely. I totally agree. It's about getting out of your comfort zone and making that first step. Once you say, "Hello," and you introduce yourself, after that things are much easier. People are always going to befriend you, like 99 percent of the time.

Mary Loubele: Yep. That's true.

Kirill Eremenko: That's good. Okay. Great advice there.

I guess I would summarize that as ... have a social component in mind. Don't focus on it at too much, just let it happen. But also encourage people to converse with each other and maybe outline the importance and value of networking.
Mary Loubele: Yep. That's true.

Kirill Eremenko: Okay. What are some of the tips? ... On the opposite side ... this is good one? What are some of the tips for going to first meetup?

So, somebody who hasn't been to the first meetup? Where do you discuss that as valuable and what value they can get out of it? Why it's important, but what are tips for a person going for the first time? Should they bring a pen and a paper? Should they bring their laptop? Should they bring some water?
We already talked about socializing; that's important. But, what else?

Mary Loubele: Depends. If you need to, bring your laptop for most of the sessions that actually will say that it's a hands-on or something. Otherwise, you're probably fine without your laptop. It's always easy to have some paper with you, otherwise some business cards also might be helpful. Make sure you've set up your LinkedIn. You easily can connect with people, or take a picture of peoples' badge.

Kirill Eremenko: That's a good one. Yeah.

Mary Loubele: [crosstalk 00:29:51] For best, you also have to think, "Everybody had already been once, the first time," at a meetup, so there's no need to be afraid about it.

Kirill Eremenko: That's a good tip, especially about the LinkedIn. I think that's very important. Guys, if you're listening to this and you don't have LinkedIn yet, make sure you get one very soon. It's very, very important.
Okay. Tell us a little bit about your personal side of things. What is one of the biggest accomplishments that you've had through your meetup?

Mary Loubele: The big accomplishment would be like the story I just mentioned about -

Kirill Eremenko: Ahhh, the trip to San Francisco.

Mary Loubele: The trip to San Francisco, but it also allowed me to grow my network here locally in Canada, because when I moved over from Belgium, I didn't know anyone here, so it's best for me ... a way to get know more people, and also a way for people to get to know me, which allowed me to land also, better jobs, and find better opportunities.

Kirill Eremenko: Oh, interesting. So going to a meetup helped you network, and help you land better jobs.

Mary Loubele: Yeah. That's true.

Kirill Eremenko: Wow. You should have started this whole conversation with that. That's what people are after.
Okay. Great. That's awesome. You hear that guys? Networking obviously can lead to more opportunities and meetups is the best way to do it, because you're already in that city. You're already interested in job opportunities in your city. So, yes you can connect with people online, which is great, but if you want to guarantee that they're in your place, in your location, then meetups will put that filter in place for you.

Mary Loubele: The important thing for this is also making sure that you're actively participating, either, for example, for talks, or helping organizing. Because, that way you get noticed more than just like going there to a meetup. It also just shows that you can give.

Kirill Eremenko: You can get value, add like ... you'll be proactive.

Mary Loubele: Yeah. At the meetup, you're proactive, which is indeed important. Also, it rather helps out for me is being able to share my story with other people, so you can connect with other data scientists. It's also like a challenge. At a company, for example, you'll only much be with a small group of data scientists. For example, if you are as startup, you might be the only data scientist.

Kirill Eremenko: Yeap.

Mary Loubele: That's also important, that you keep connecting with people of similar interests. That you can learn extra from them. And also if you are actively organizing it, you also get more confidence, which is also important for your jobs.

Kirill Eremenko: Yeap. Totally agree. Totally agree.

So, definitely worthwhile. Especially if it's only once or several times a month, or even once a week. It's not that much. It's not going to take up that much of your time. I'm sure there're places in your life where you could be a bit more efficient and save some time to then spend it on something like this that has so many benefits which we've discussed.
Mary Loubele: Yeap.

Kirill Eremenko: Okay. Any other ways actively participating in meetups can help grow your career? We've talked about through learning together and being able to overcome challenging topics that you wouldn't be able to overcome on your own. Also, we talked about meeting people for networking with them and potentially getting more job opportunity.
Anything else that comes to mind?

Mary Loubele: What actually might help out there is having more efficient meeting styles.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: For example ...

Kirill Eremenko: Oh, that's a good one. So, you will take away ... sorry to interrupt, but I'm just thinking out loud. You'll take away those skills that you'll learn at a meetup.

Mary Loubele: Yeap.

Kirill Eremenko: And you'll apply them at work.

Mary Loubele: Yeap. That's true. Like for example, if you are participating in a bigger group, you'll learn different ways people are negotiating, which is important. Also, for example, you need to find sponsorship.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: - for the meetup, which is also important skill to learn. Because of the Intersections, we now have meetup in Montreal, so that's also for me to learn how can I actually scale what I've learned here locally at a city which is six hundred kilometers away.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Also, an interesting challenge is that I'm working with communities that are a bit further away.

Kirill Eremenko: Mm-hmm (affirmative)-
So you're planning on doing a meetup in Montreal, though?

Mary Loubele: I recently did one already.

Kirill Eremenko: Oh, Okay. Did that go well?

Mary Loubele: It went well. We had like 30 people showing up, but once again, where the Elasticsearch talk that I was giving there was pretty fun.

Kirill Eremenko: Okay. Okay. That's very cool.
Okay, and so you use the Meetup.com platform for these meetups, is that correct?

Mary Loubele: Yep. That's true.

Kirill Eremenko: Is it convenient? How are you finding it?

Mary Loubele: It is convenient because it is suggesting through data science your meetup to people with similar interests.

Kirill Eremenko: Uh-huh (affirmative)-

Mary Loubele: In that way you can actually get extra members, which is a benefit. And also, yourself, you also get suggestions on meetups that might be interesting for you.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: So it's an extra way for connecting with other people.

Kirill Eremenko: That's cool. I recently started using Meetup.com, and I find it quite useful as well for ... especially when you're like ... at the same time it's a bit too much. I sign up for one meetup for rock climbing, and now all I get is rock climbing and hiking recommendations. I'm like, come on. There's gotta be something else in this city that's interesting.

Mary Loubele: Otherwise, what you can do is just the meetup group of your students, and then you will get data science recommendation in your city.

Kirill Eremenko: Okay. Yeah. That's a good one. That's a good point.
Okay. Alright. Well, that a good little excourse into the world of meetups. Thank you so much for that. I think that will be helpful for lots of people that have never been to a meetup or that have never organized a meetup. I think there's some useful advice on both fronts, there.

Kind of like slowly coming to an end of the podcast, what do you say is the next important or major milestones in your career as a data scientist or in your work with meetup groups? What are some of the things you're looking forward to?
Mary Loubele: For my career is trying to grow more in a leadership role, that I can actually mentor more people. And for, meetups, what I would say there, is needs working [inaudible 00:36:50] with other cool organizers. Again, mentor to people more, and give ideas and that I not need to focus too much myself on doing all the organizing myself.

Kirill Eremenko: Mm-hmm (affirmative)-

Mary Loubele: Also, maybe having some bigger events where we can get like 100 people showing up. Which would be great!

Kirill Eremenko: Yeah. That's cool. Well, that's a great aspiration. By the way, I never asked ... what city are you in, in case somebody's interested in coming to your meetups or just to get in touch with you a bit closer?

Mary Loubele: It's Kitchener Waterloo, so we are like 100 kilometers away from Toronto in Canada.

Kirill Eremenko: Okay. Kitchener Waterloo. You told me, I remember at the start, that it used to be two cities and then they grew together?

Mary Loubele: It's still two cities, but they're like really close together, and they're just called Kitchener Waterloo. It's also because in Waterloo, they have the university, but Kitchener is actually the bigger city.

Kirill Eremenko: Oh. Okay, gotcha. It reminds me of the story of Budapest. Before, it used to be two cities, two separate cities, and now they've grown together. Well, quite a while ago they've grown together, but now it's Budapest. It's one city. Interesting.

Mary Loubele: Yes. It's actually a really beautiful city.

Kirill Eremenko: Yeah. Have you been?

Mary Loubele: Yeah. I've been there twice.

Kirill Eremenko: Okay.

Mary Loubele: A long time ago. But, I enjoyed it lots.

Kirill Eremenko: That's nice.
Well. Thank you so much for coming on the show. It's great having you here.
What would you say are some of the best ways for our listeners to get in touch with you and to follow you, and maybe get in contact about the meetup?

Mary Loubele: They can definitely contact with me on LinkedIn or otherwise they can follow me on Twitter.

Kirill Eremenko: Mm-hmm (affirmative)-
Okay. Cool. We'll put those in the show notes.

Mary Loubele: Okay.

Kirill Eremenko: What is your Twitter, by the way?

Mary Loubele: loub_m.

Kirill Eremenko: Okay. Gotcha. And the meetup is called Intersections-KW, right?

Mary Loubele: Yeah. That's true.

Kirill Eremenko: Okay. Gotcha.
Alright. Thank you so much. One more question I for you today, I have. What's a book you can recommend to all of us?

Mary Loubele: Designing Data-driven Applications.

Kirill Eremenko: Why ... is that a good book to read?

Mary Loubele: Because it's covering the different aspects of data-engineering and it's really starting from the beginning and how you can model your data, how you can use sequel, or how you can use no sequel basis. It's covering parts of our [inaudible 00:39:22]time, and eventually covering what the future of data engineering will look like.

Kirill Eremenko: So Designing Data-driven Applications, was it?

Mary Loubele: Yeah. That's true.

Kirill Eremenko: Okay. Once again thank you so much for coming on the show. It was great to learn about the world of meetups and how people can get into it. Guys, if you're listening to this, then definitely check it out then. Also, connect with Mary on LinkedIn and Twitter.
Thank you, Mary. It was a pleasure.

Mary Loubele: Also a pleasure chatting with you.

Kirill Eremenko: So, there you have it. That was Mary Loubele, a data science meetup organizer from Canada. I hope you enjoyed today's podcast and got some valuable insights. Definitely if you're looking to organize a meetup there were some valuable tips there. And, mentioned in the podcast, I'm seeing that more and more people are starting to organize data science meetups in their areas.
I guess it's because it's such a great way to connect, learn together, and, you know, just feel how your part of a community, feel like your part of something much bigger than yourself on your own.

So, if you would like to get into a data science meetup, then head over to Meetup.com, and you can look them up there in your area. I highly encourage doing that. At least once a month, would be ideal. But, even if you could do it once a year, four times a quarter, that's already going to be very beneficial for your career and we outlined some valuable points why that would be very beneficial in today's session.

Also, you can get the show notes for this episode at superdatascience.com/157 There, we'll include to Mary's LinkedIn, and you can connect with her there. And of course, if you have any questions on how to organize your first meetup, I'm sure she'll be happy to help you out and assist with any additional information and insights.
On that note, thank you so much for being here today. I look forward to seeing you next time. Until then, happy analyzing.

Kirill Eremenko
Kirill Eremenko

I’m a Data Scientist and Entrepreneur. I also teach Data Science Online and host the SDS podcast where I interview some of the most inspiring Data Scientists from all around the world. I am passionate about bringing Data Science and Analytics to the world!

What are you waiting for?

EMPOWER YOUR CAREER WITH SUPERDATASCIENCE

CLAIM YOUR TRIAL MEMBERSHIP NOW
as seen on: