The histogram is a very useful visualization tool, and you need to master it.
In the world of data visualization, the heatmap is underrated and underutilized. It has limitations, but overall, it’s an excellent tool in your data science and data visualization toolkit. After you’ve mastered the foundational visualization techniques (you can write the code for the basic plots in your sleep, right?), you should learn the heatmap. […]
Most people woke up on Wednesday morning to some combination of shock, joy, bemusement, and/or mild terror as Donald Trump unexpectedly won the presidency.
I say “unexpectedly” because …
The world has just entered one of the biggest transitions in history. That’s the contention of two MIT economists, Eric Brynjolfsson and Andrew McAfee. In their recent book, The Second Machine Age, they argue that big data, computation, and innovation are changing our economy and institutions with a magnitude greater than almost anything ever seen […]
A few weeks ago, an acquaintance told me that he was interested in getting started with machine learning. He’s a web developer who primarily works in Ruby and Python, but also has a small amount of experience with R. Day-to-day, his work is run-of-the-mill web development, and he’s confessed to me that he’s a bit […]
Claims of “the end of geography” and the flatness of the world notwithstanding, place still matters today. Discussing why place matters is somewhat beyond the scope of this post, so I will direct you to the excellent work of Parag Khanna and his book Connectography. To put it simply, the the future of business and […]
In part 1, we went over how to use data visualization and data analysis prior to machine learning. For example, we discussed how to visualize the data to identify potential issues in the dataset, examine the variable distributions, etc. In this blog post, we’ll continue by building a very simple model and using data visualization […]
In my last article, I stated that for practitioners (as opposed to theorists), the real prerequisite for machine learning is data analysis, not math. One of the main reasons for making this statement, is that data scientists spend an inordinate amount of time on data analysis. The traditional statement is that data scientists “spend 80% […]
When beginners get started with machine learning, the inevitable question is “what are the prerequisites? What do I need to know to get started?” And once they start researching, beginners frequently find well-intentioned but disheartening advice, like the following: You need to master math. You need all of the following: – Calculus – Differential equations […]
Over the last few blog posts, I’ve discussed some of the basics of what machine learning is and why it’s important: – Why machine learning will reshape software engineering – What is the core task of machine learning – How to get started in machine learning in R Throughout those posts, I’ve been using the […]