a tumblelog
30 Mar 2020

When to assume neural networks can solve a problem

Thus, I thought it might be helpful to lay down the heuristic that generates such answers. I by no means claim these are precise or evidence-based in the scientific sense, but I think they might be helpful, maybe even a good start point for further discussion on the subject.

Source: When to assume neural networks can solve a problem.

The iPad at 10: Emerging from the Shadow of the iPhone

The 10th anniversary of the iPad isn’t a destination, it’s just an arbitrary point from which to take stock of where things have been and consider where they are going. To do that, it’s instructive to look at more than the endpoints of the iPad’s history and consider what has happened in between. Viewed from that perspective, the state of the iPad ten years later, while at times frustrating, also holds reason for optimism. No single product in Apple’s lineup has more room to grow or potential to change the computing landscape than the iPad does today.

Source: The iPad at 10: Emerging from the Shadow of the iPhone, an article by John Voorhees.

How to Use any() in Python

As a Python programmer, you’ll frequently deal with Booleans and conditional statements—sometimes very complex ones. In those situations, you may need to rely on tools that can simplify logic and consolidate information. Fortunately, any() in Python is such a tool. It looks through the elements in an iterable and returns a single value indicating whether any element is true in a Boolean context, or truthy.

Source: How to Use any() in Python, an article by Alex Ronquillo.