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Jack Kwok is a Software Engineer with 15 years of professional experience. At Insight, he built a Deep Learning solution to automatically detect flooded roads during natural disasters. He is now a Software Engineer at Lyft working with Machine Learning and Deep Learning. Want to learn... Read more
Health + Tech Perspective : Access to Symptoms > Better Algorithms
  Here’s a dangerous meme that I keep running into: “A doctor’s job is basically to look at symptoms, make a diagnosis, then prescribe treatment. Medicine is just a big decision tree — ripe for optimization and automation.” Of course, it’s mostly my friends in tech saying these... Read more
A probability on its own is often an uninteresting thing. But when we can compare probabilities, that is when their full splendour is revealed. By comparing probabilities we are able form judgements; by comparing probabilities we can exploit the elements of our world that are probable;... Read more
Machine Learning vs. Statistics
This was originally posted on the Silicon Valley Data Science blog was co-written by Drew Hardin   The Texas Death Match of Data Science. Throughout its history, Machine Learning (ML) has coexisted with Statistics uneasily, like an ex-boyfriend accidentally seated with the groom’s family at a wedding reception: both uncertain... Read more
Ethics for powerful algorithms (3 of 4)
(Hi, all! Apologies for the long radio silence — my day job has been all-consuming. For those of you joining us for the first time, this series is about the controversies/risks/concerns around using algorithms in the criminal justice system. You might want to check out my first post here,... Read more
This blogpost is about topic modeling using data from this blog, opendatascience.com. From this, combined with the most visited articles of the year, we will generate the most popular topics of 2017. Last year, we did something similar with popular articles streamed through twitter using Non-Negative Matrix Factorization to... Read more
Watermain Breaks in the City of Toronto
It has been a while since my last post due to the major transition of moving back to Canada. This post will be a bit shorter than my previous ones but hopefully it will give some insight on practically investigating and analyzing open data that are... Read more
The normalcy of online learning: the more you study, the better you do
Online learning, after all, is just a form of learning: time spent studying is one of the best predictors of success. Both the pattern (and the exceptions) can be seen quite clearly on the Open University Learning Analytics dataset, which collects anonymized data about the personal characteristics and,... Read more
What’s the difference between data science, machine learning, and artificial intelligence?
When I introduce myself as a data scientist, I often get questions like “What’s the difference between that and machine learning?” or “Does that mean you work on artificial intelligence?” I’ve responded enough times that my answer easily qualifies for my “rule of three”: When you’ve... Read more
Ethics for powerful algorithms (2 of 4)
This is the second of four articles on the ethics of powerful algorithms, taking COMPAS as a case study. Our story so far: COMPAS is an algorithm used widely today to predict which criminals are most likely to commit future crimes. Investigative journalists at ProPublica recently published a... Read more