Rather than dig into complex math or over-simplify by using a pre-written function, we'll write our own binomial test function, primarily using base Python. In the process, we'll learn more about how hypothesis testing works and build intuition for how to interpret a p-value.
IaC allows developers to supply IT environments with multiple lines of code and can be deployed in a matter of minutes (in contrast to manual infrastructure, which can take hours if not days to be deployed).
In order to get the most performant site possible when building the codebase for our public Stack Overflow site, we didn’t always follow best practices.
While many introductory statistics classes teach the CLT, very few actually attempt to prove it because that requires some complex math. In this session, we'll bypass all that math by using Python loops to simulate the CLT.
Comparing summary statistics like the mean and median can help us understand how these variables are related, but we can learn even more by using visualizations.
One of the tough decisions you and your team may face as you scale is deciding between keeping your current codebase and rebuilding on a new architecture.
Single page apps are all the rage today, but they don't always operate the same as traditional web pages.
Investigate a dataset with summary statistics and some basic data visualizations using the Python libraries NumPy, pandas, matplotlib, and Seaborn.
When it comes to developing low latency software systems, the received wisdom is that you would be crazy to use anything but C++ because anything else has too high a latency. But I’m here to convince you of the opposite, counter-intuitive, almost heretical notion: that when it comes to achieving low latency in software systems, Java is better.