Even working in splendid isolation there have been times when I managed to lose a prior version of my code that actually worked better, and I wished I could get back to it without having to re-think everything from scratch! Now that I'll be collaborating with others, version management is going to be a big... Continue Reading →
This morning I've been playing "spot the difference" - a simple enough task: use a bash shell script to get 2 strings from a user (first name and second name) and then evaluate whether the 2 strings are the same or different. I had a template for the script and everything from the edX course,... Continue Reading →
Today I'm ploughing my way through the edX Introduction to Linux and found myself wondering "whyyyy??". It's all quite entertaining and nifty, but how will I be using this later? Naturally I googled (using bing!) and found this wonderful online resource www.datascienceatthecommandline.com. After reading the section entitled "A Real-world Use Case" involving data for New York... Continue Reading →
Alexander Pope is famously quoted as saying: A little learning is a dangerous thing; drink deep, or taste not the Pierian spring: there shallow draughts intoxicate the brain, and drinking largely sobers us again. I've been thinking about these words the past few days as I worked on my latest challenge: a text classifier using... Continue Reading →
I had an email today from a reader ("K") who tried the Learn Python Challenge on Kaggle and (as does happen!) got to about Day 4 and then abandoned ship and went in search of more new stuff... The question is how to keep on going - when you get stuck, bored, de-motivated or perhaps even... Continue Reading →
I signed up for this 7-day challenge to test my knowledge, and it's been an absolute delight! As a newbie, when I find myself on StackOverflow reading discussions about "the most Pythonic way" to do something, I usually feel a bit left out... I'll just be happy if I can do it any darned way... Continue Reading →
So stoked to be attending Data Science Intensive later this year - "first of its kind in Africa": 8 weeks solving real world problems, I can hardly wait :).
This week I'm literally feeling like a magician! My first real classifier attempt: with a month's worth of emails to the Service Desk, and sklearn.naive_bayes ,I can tell to a 96% certainty which incidents should be assigned to Team A and which to Team B. MAGIC!
As a newbie, I've been receiving files via email, copying them to my Jupyter Notebook folder, running my script, emailing the resulting outputs back to my customer. As a prospective data scientist I've been feeling positively embarrassed about this ridiculously low-tech process! Thanks to my colleagues Shaun and Christine, I've been set onto the path... Continue Reading →