I do a great deal of work with strings — while most of what I do is via natural language processing (NLP), I frequently just have to count the number of instances of a substring that exist within a string and the Python count() function is an elegant, simple, and effective way of doing just that.

How It Works

How it works is really the best part — you just use a string object and call count() giving it the string you want to count. By way of example, assume you have the following log file (adapted from a sample IBM log file):

Robotic Process Automation (RPA) can be a very good automation option to enhance human productivity often (but certainly not always) at a reasonable price point. There are several options available including UiPath but before you spend all kinds of money (UiPath is not inexpensive), you can see what it can do and if it can help your intelligent automation efforts by test driving the UiPath Community Edition.

To their credit, for educators and students (and anyone can be a student not just actual students), Community Edition is a free, fully functional version of UiPath Studio and here’s how you can…

I was tired of shaking hands and kissing babies and wanted to make more than money — I wanted to make a difference. I had spent over a decade in executive positions that I thought were what I wanted, but they left me an empty shell of a person and I just wanted to get back to doing something I loved doing. So, I reinvented myself.

That sounds really nice and theatric, doesn’t it? It’s mostly nonsense (the empty shell part is true). I really wanted to make more money by understanding data science as an executive, which is why…

I’m not gonna lie, I really dig spaCy; it’s based on sophisticated natural language processing (NLP) but is incredibly simple to use. It’s an ML engineer’s dream (what a weird dream though). Separately, it’s also a data scientist’s dream because of how the underlying NLP can be enhanced (still a weird dream)! I get to use it almost every day and along the way, I’ve picked up a few tricks you might find helpful, the first involves reusable terms.

Rule Matcher Basics

One of the core ideas in spaCy (really NLP) is that words are broken down into tokens and those tokens can…

When data doesn’t reflect a “fair” reality do we change it to meet our ideal?

Perhaps the most dangerous bias is when we presume we have no bias — and everyone has bias. If you think you’re the one person without bias, you may want to re-read that last sentence a few hundred times. Biased is based in part on experiences, which create pre-judgements (doesn’t that sound a bit less harsh that prejudice?) or stereotypes¹ and we unconsciously validate those pre-judgements because of confirmation bias¹. …

Robotic process automation (RPA) tools have come such a long way since “macros,” but in some situations, their functionality can be taken too far, which can result in vendor lock-in and getting a less-than-best-in-breed experience. Here’s one way to keep your options open and keep systems that control user interfaces separate from programming languages that control everything else.

The main idea is to very clearly separate UI interaction and programming along UiPath and Python dimensions. The very good news is that UiPath natively supports this design, and you’ll soon see why it’s such a good idea.

Disclaimer #1

While I’m going to…

What’s Julia?

For starters, Julia is not an actor or even a person. It’s a programming language and according to its creators, Julia fills a gap between easy prototyping and performance:

“The Julia programming language fills this role: it is a flexible dynamic language, appropriate for scientific and numerical computing, with performance comparable to traditional statically-typed languages.”

Hmmm. That’s interesting and while I have found many ways around Python’s performance (e.g., Azure), it’s exciting to think maybe I can train a model in less time on my workstation.

Why Am I Doing This?

I really love Python. It’s easy, there’s an amazing ecosystem (via PyPi), and I…

I’m a competitive person by nature (or nurture, you pick) and I can’t help but wonder if I can beat PyCaret at machine learning. There’s really only one way to find out — have a competition!

The Rules

My bias is already going to be almost overwhelming considering how badly I want to beat the machine, which means I need to establish some ground rules so it’s a least a fair fight (I imagine PyCaret is giggling to itself right about now). Here are the ground rules:

• The same data is provided to both competitors
• The ‘out of the box’ settings are…