Image by krzysztof-m from Pixabay

I started using Google Cloud about 2 years ago, and it is pretty amazing. GCP comes with lots of features for building data pipelines, and it has great integration with Looker for visualization. Streaming live data into BigQuery through Pub Sub and Dataflow is quite straight forward. If you have…


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It’s a bright and sunny day. You start up a Jupyter notebook, browse around your data, and then try to build some nice charts. Basic bar, line, yadi yadi yadda, piece of cake! You got an initial chart quickly but wait… a lot of ways to make it better still…


Photo credit (Daniel Tuttle)

While working with production data, one issue I have seen multiple times is that the dataset have a large amount of columns, but only certain ones are meaningful. You can certainly filter explicitly by columns, if you know which exact column you want. But often times I realize I just…


Data marching one by one

The goal of this article is simple. There are a few common patterns that I’ve now realized is quite useful. Applications need to publish, probably large amounts of it, and you want to store it in the cloud and for analysis or machine learning purposes. Google cloud is quite powerful…


My Pomeranian yawning

After a few months of wrangling and cleaning data, building machine learning pipelines, and implementing recommendation engines, we’ve now arrived at the finale. As I progressed through this data science degree, all of the exercises and projects were invaluable in polishing up my Python skills. I did many hands on…


Credit: Mykola Holyutyak/Shutterstock.com

Whatever job you are in, whichever industry, however many years of experience you have, someone at your office is mentioning data science and machine learning. …

Ronald Leung

Senior Engineering Manager at NCR

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