Oftentimes Times Series lessons can focus mainly on the application of statistical tests and the creation of forecasting models. However, I find this assumes a lot about the competency level of readers. …

For a lot of us, finding the greatest common denominator between numbers was a common exercise in grade school math. However, in the real world finding GCDs can form an integral part of our algorithms and analysis. …

Duplicate detecting and indexing is a fundamental skill every data scientist should have. When dealing with any dataset, it is important to identify and locate values that are identical. In this article, we shall take a look at several techniques you can use.

Let’s get started!

So let’s say you…

One of the challenges of being a data scientist is solving unique problems that leave most people scratching their heads. These range from seemingly innocuous textbook exercises to complex riddles left unsolved for years. In this article we shall go over some light to intermediate problems that will help you…

List comprehension is a powerful tool that allows Python programmers to write codes in an extremely condensed fashion. In this article we will go over how to use list comprehension to simplify otherwise complex functions.

Let’s begin!

To start off, let’s create a sample string.

`sample_string = 'sample_for_list_comprehension'`

Now let…

One of the most interesting aspects of the Python language are Lambda functions. For programmers who are skilled at reducing their codes into simple logical statements, Lambda functions help shrink the number of lines dramatically. …

Python is an excellent language for new programmers to learn. Its intuitive nature makes it easy for most people to quickly understand what the codes and algorithms are actually doing. In this article and many others in the future, we will be going over the many ways one can use…

One of the most important skills a data scientist can learn is how to craft a convincing story using the given data. Though we tend to think of our work as being objective and technical, encapsulated in the adage “Numbers don’t lie”, we should also be aware of its more…

In a previous article, we explored the idea of applying the K-Means algorithm to automatically segment our image. However, we only focused in on the RGB Color Space. …

So far most of the techniques we’ve gone over have required us to manually segment the image via its features. But we can actually use unsupervised clustering algorithms to do this for us. In this article we shall go over how to do just that.

Let’s begin!

As always, we…