All about high-intensity interval training, written by a robot.

Last month I wrote a blog about some artificial intelligence powered copywriting services.

Now that one of these services has released its blog functionality, it’s time for a follow-up. To give the robot writer a better chance, I’m using a topic with plenty of background material — fitness, specifically high-intensity interval training.

Aside from the intro, the remainder of this blog was written by a real-life robot. The blog was generated by Copysmith. You can find more about this service here.

High-intensity interval training (HIIT) is a great way to improve…

Big O Notation is a way to measure an algorithm’s efficiency. It measures the time it takes to run your function as the input grows. Or in other words, how well does the function scale.

There are two parts to measuring efficiency — time complexity and space complexity. Time complexity is a measure of how long the function takes to run in terms of its computational steps. Space complexity has to do with the amount of memory used by the function. This blog will illustrate time complexity with two search algorithms.

Big O is sometimes referred to as the algorithm’s…

This blog will cover Word Clouds, their limitations, followed by some formatting examples.

Word Clouds are a straightforward way to summarize text and make the most popular words jump to your attention. They are eye-catching and easy to understand without the need for any additional explanation.

However, Word Clouds do have limitations. They are not helpful for an in-depth analysis. They may be more attractive to look at than a simple bar chart — but they provide far less information. Here are some of the problems with Word Clouds.

- Font size is not an effective way to show differences. We…

Here are three tricks to enhance your YouTube learning experience.

YouTube has over 2 billion monthly users. Every day people watch more than a billion hours of content. More than 500 hours of content are uploaded every minute*. So, chances are you’ve seen a thing or two.

And it’s not just for entertainment. YouTube is now the world’s second-largest search engine, so it’s an essential tool for learning. …

Excel is one of the most widely used software packages in the world. It has been around since 1985 and has approximately 750 million users. Microsoft likes to call Excel formulas “the world’s most widely used programming language.”

Excel is great at doing simple analytics and helping people make sense of numbers. It is amazingly flexible and versatile. Excel is popular with users but often less so with IT departments. …

When we learn how to multiply, we learn to split the equation into parts. First, we find the product using the ones place value. Then we move to the tens, followed by the hundreds. Finally, we sum everything up and arrive at our answer. This method works great, but it’s not always the most efficient. Here are a few other methods that can speed up the process.

In these examples, I am using 2 and 3 digit numbers. These methods also work with larger numbers.

Draw a grid and split each square with a diagonal line. Write one number along…

The first trick is to simplify your problem by breaking it into smaller pieces. For example, we can rewrite

`567 + 432 `

= 567 + (400 + 30 + 2)

= 967 + 30 + 2

= 997 + 2

= **999**

It’s often easier to work with adding a smaller number, so instead of 131 + 858, swap the numbers

`858 + 131 `

= 858 + 100 + 30 + 1

= **989**

Using the complement of a number can help make subtraction easier. …

The Holy Grail for Lazy Marketers?

Following the launch of GPT-3 last year, some notable use cases have been developed. This blog will demonstrate examples from five new services that generate text and write copy for you using artificial intelligence.

*Generative Pre-trained Transformer 3 (GPT-3) is a language model that uses deep learning to generate intelligent text that is almost indistinguishable from text written by a real-life human. GPT-3 was created by the research lab OpenAI. The scale of GPT-3 is awe-inspiring. It was trained on a massive amount of text, with more than 175 billion parameters. …*

The Content from Subscription Streaming Services Now Adds up to 27 Years

I’ve taken a couple of shots at estimating total streaming content already. With the launch of Discovery + bringing thousands of additional episodes to the market, I thought that it’s time for an update.

This edition is more of a research project than data science. Wherever possible, I’d look for numbers from the streaming companies themselves. The trouble is that companies vary a great deal in their estimates. Some talk about the hours available on their service, some the shows, some the episodes, and some the movies. …

These are a few tricks that I’ve found helpful. Hopefully, you will too.

So you’ve loaded up a Dataframe and are ready to explore. Along with the usual ways of taking a first glance at your data …

`df.info(), df.describe() and df.shape`

I like to look at what is inside the columns as well. This simple loop will give you a count of how many unique values there are in each column.

`# number of unique values in each column`

for column in df:

print(column, df[column].nunique())

Example output

`bedrooms 9 bathrooms 24 sqft_living 568 sqft_lot 3778 yr_built 116 zipcode 70…`

Andrew has an analytics background with over 20 years of experience in various industries, working with world-leading brands.