Life is a Journey
It took me a while to finally complete all 17 modules, but knowing that there was a clear outcome helped motivate me to keep taking the next step, and the step after that.
So, if you’re interested in getting a taste of what the world of machine learning has to offer, beginning with the (free!) online courses on Kaggle Learn is a great starting point. I know that it definitely was for me.
Continue readingPart 2 of my Kaggle learning journey focused on the data-centric modules. The tutorials and hands-on coding exercises were rich in content and spanned across Pandas, Intro to SQL, Advanced SQL, Data Cleaning and Feature Engineering. 13 down, 4 more to go!
Continue readingLast August, I completed Kaggle’s “30 Days of Machine Learning” challenge. In the spirit of continuous learning, I decided to take the plunge and finish all the remaining 14 modules in Kaggle Learn. It took me another 30 days, over a span of several months, to finally read through all the tutorials and complete all the coding exercises. Here is Part 1 of my learning journey.
Continue readingTo determine how bad the situation had gotten, I decided to do a one-off stock take of all the alcohol in our apartment and compile a complete inventory. It looks like we currently own 24 litres of alcohol.
Continue readingHot off the heels of some geospatial visualisation that I built using global coffee production data in 2020, I wanted to see if I could use all the data available from 1991-2020 to render a bar chart race. It turned out to be surprisingly simple. Here’s what I did.
Continue readingAfter completing Kaggle’s Geospatial Analysis course, I decided to try out my newly acquired skills by applying them on a dataset outside of Kaggle. Since I’m such a coffee addict, why not combine my two interests and do some geospatial visualisation on global coffee production?
Continue readingImmediately after completing Kaggle’s “30 Days of ML” challenge, I started on their “Intro to Deep Learning” online course which was estimated to take four hours to complete. It was definitely time well spent.
Continue readingLast month, I received an email from Kaggle inviting me to participate in a beginner-friendly “30 Days of Machine Learning” challenge. It was a timely reminder to continue on my data science learning journey, especially since I haven’t made any progress for quite some time.
Continue reading“A Whirlwind Tour of Python” by Jake VanderPlas is a handy little reference for those with some prior programming experience but who are new to Python. It is compact (only 98 pages) yet feature rich, and is a good starting point for picking up Python.
Continue readingOne unexpected benefit of joining Kaggle was the discovery of an introductory Python course on Kaggle Learn. It is free to use and consists of short tutorials and hands-on notebook exercises that highlight the key aspects of the language.
The course has a focus on data science applications and is targeted at those with some prior coding experience.
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