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The Women in Machine Learning Program Blog Series Part 7 – Brooke Clarke

We are publishing a blog series on the brilliant women we had involved in the Women in Machine Learning program last year.  

Whoever you are, and whatever your background we are sure you will find their thoughts on Machine Learning, inclusion and their stories inspirational and inspiring.  

Brooke Clarke

Brooke is a community powerhouse. Most nights you’ll catch her at one of the Melbourne technical meetups. She also posts programming tutorials and notes on her Data Science journey on her blog Girl vs. Data. Since completing the Women in Machine Learning program, she has gone on to successfully apply to EA (Electronic Arts for the non-gamers out there) to join their team as a Data Analyst.

What gets you excited about Machine Learning, and what makes you want to learn more?

I first found out about Data Science a couple of years back, when I was working at EB Games Head Office and a big part of my job was making reports about how our sales and trades were going with our pre-owned products. I had just realised I could automate my Excel reports with VBA Macros, and at the same time I’d just come across SQL Server and found out that I could dig into even more of the data without being constrained by someone else’s pre-chosen filters for their queries.

I was addicted, I was constantly learning and finding out about new things and new ways to work with data; and the insights coming from this data were really doing massive things to help out the company I was working in. From there I started learning about forecasting and predictive models, I started listening to Data Science podcasts and hearing about Machine Learning, AI, and Deep Learning.

I think one of my favourite parts of learning to code something new, is being able to watch all of the puzzle pieces come together as you’re building it. I’ll just look at something that I’ve never tried before and grab some code and just work through it until I can understand why it does what it does. With Machine Learning, I’m doing that, but it’s with this really cool, intelligent new technology that has a unique way to unlock this untapped potential of so much data. It’s got kind of a fantastical kind of Sci-Fi appeal to it, I can’t help but get excited that I’m one of the lucky people who gets to play with it!
 

What diversity initiatives would you like to see in the MLAI industry?

There’s a few organisations around Melbourne that are doing great things for diversity and specifically, women in tech. I think we can do more for the MLAI industry, seeing as forecasts of skills shortages in Australia have become something of a regular occurrence on the news recently; so we will need as many passionate skilled workers as we can get.

I can only write honestly from my own perspective, so with that in mind, there are a few things we can do:
– More women speakers at conferences, and more diversity in panels. I’ve been hearing the phrase “You can’t be what you can’t see” passed around a lot lately, and it’s absolutely right. Seeing people like you speak at conferences or events is hugely beneficial to everyone at the start of their careers. It gives you something to strive towards, and helps to find people who share the same passions and the same struggles.
– Teach young girls about the huge range of tech career options available to them. I hadn’t even heard of Data Science until about 3 years ago, and until then I had never even considered a career in programming. I wanted a creative tech career, and I had assumed the only options for me had to do with design, illustration and 3D animation, because these were all I was exposed to in school. I wish I’d learnt how creative coding could be!
 

What was your favourite part of the Women in Machine Learning program, or what did you get most out of?

It’s hard to pick just one favourite thing, but the sheer number of intelligent, talented women that were part of the program was definitely a major highlight. I spoke with a full stack developer, someone working on their PHD, another woman working in cancer research, and a student who’s just received a young achiever’s award; and that’s just one small sample of the caliber of women in the program. I found by the end of the 2-day Deep Learning workshop that I’d learnt just as much from the cohort of women working around me as I had from our presenters.

What is next for you on your Machine Learning journey?

Well 2018 was a massive year for me. Apart from being part of the Women in Machine Learning program, I competed in the Data Science Melbourne Datathon for the first time, and my team got 4th place (super proud!); I presented my first ever talk at the PyLadies and MLAI meetups (which was one of my big 2018 goals); and I scored myself an amazing new position as a Data Analyst at EA (Electronic Arts).
 
This year, I’m hoping to continue with the momentum and do some more presentations. I’ll be presenting a talk on data prep at the WiMLDS Meetup in March, hopefully with some more to come throughout the year. I’m Planning on giving DSM Datathon another go, and seeing if we can break the top 3; and I would also love to start a Masters in Data Science this year, so we’ll see how that goes. 
 
I’m loving my new job, and it’s very data heavy, so I’m hoping I’ll be able to keep brushing up my skills so I can inject a little more Machine Learning & Deep Learning into my work day!

What advice do you have for anyone from an underrepresented group in entering a career in tech?

Let your passion guide you, and you’ll find your way. There are people like you out there, way more than you would ever expect! If you are honest with yourself and speak with your passion, you’ll find them.

Some of the amazing communities that I’ve found myself a part of in just the last 12 months or so: PyLadies Melbourne, Girls in Tech, Women In Machine Learning and Data Science, Code Like a Girl. I found out about Silverpond’s Women in Machine Learning program at the first PyLadies meetup I went to!

I’ve found that going to meetups and engaging with the community is really the best way to not feel like you’re the only person going through the unique circumstances that meet women in tech. Plus there are just so many talented women out there that I am learning from and building connections with, I’m excited to watch their careers evolve alongside mine!

 

Do you or your company what to support the Women in Machine Learning  program in 2019? Register your interest here. 

We will be opening applications for the Women in Machine Learning program later in 2019. Register your details here to be amongst the first to apply.

Interested in a career in Machine Learning? We are hiring, check out our current openings here.  

Did you enjoy reading Brooke’s post? Check out the rest of our Women in Machine Learning blog series…

Part 1
Part 3: Ashley
Part 5: Georgie
Part 2: Ayesha
Part 4: Genevieve
Part 6: Millie

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