Get to know and understand some fundamentals of Data Science with this short read!


It is easy to see why one might want to enter the Data Science field in 2021. The industry has been booming now for a number of years, and only seems to continue to grow as time passes. On top of that, the job pays quite well, so both of those in tandem add up to create a pretty good career choice.

However, as much as Data Science is a burning topic and hot field, it is also a complicated one. There are so many different aspects to this discipline that it can be difficult to know where to start…

Some of Python’s strangest secrets that are much-less well-known.


The Python programming language is a programming language that is filled to the absolute brim with amazing multi-paradigm features. This is great because it gives Python the flexibility to do a lot of different tasks. For example, if Python was a purely object-oriented programming language with no support for generic programming concepts, it likely would not be quite as popular in the world of Data Science. This is because Data Scientists typically desire a high-level declarative programming language where things can be defined in a global scope. Just imagine writing a main function for a Jupyter-Notebook. …

It is easy to write bad functions, much harder to write exemplary ones — here are some of the ways I improve mine


Writing code can be a seriously difficult and challenging gig. This is especially the case when some problems are difficult to solve, and have multiple solutions. It is not always easy to keep your code in tip-top, perfect shape. This is especially the case when there are multiple solutions to one problem, some wrong and some correct. It is a well-remembered lesson when you heard your professor say “ do not ever do this.” To something that you had been doing the whole time you were programming.

That being said, while programming can be difficult, ultimately the concept of programming…

Comments are a valuable tool when used properly — this is how you should use them to be most effective.


There are many tools that a software engineer or data scientist might use in order to provide more expression to their code. There are many reasons that one might want to do this. For example, comments can be a valuable asset in a step-by-step process that needs to be taught. Comments can also provide valuable information that could be essential to working with certain code.

I think back to one example where I was having to dig through some Julia code because there was no documentation for it. I could not figure out how the input for something was meant…

Breaking the conventional methods of programming computers using Julia


In the art of programming computers, there are many different approaches to getting the job done. The “ job” in this description is interacting between types, operations (methods), and data. Historically, this has been a pretty unique realm of experimentation when it comes to computer science. The reality is that there are a lot of methods and approaches, and some are certainly better for different tasks.

That being said, Julia — for my applications, typically blows the typical look one might take at a paradigm completely out of the water. …

C Crash Course

An effective look at the structure of C syntax, and an introduction to programming with C


Likely one of the most important programming languages ever created for the history of computing is the C programming language. This language really changed the world of computers for the better in so many ways, and still plays a vital role in the world of computing today. No matter what system you are currently reading this article on, unless you printed this out for some reason, you are using C code as we speak. That being said, it is easy to understand why learning the C language could be beneficial towards your domain if you do work in any technological…

Some of the practical strategies I implement into my routine to avoid getting burnt out


In the wonderful world of programming and Data Science, it is quite common to be pushed to the absolute brink of insanity. As much as we all might love software engineering, there is certainly no denying that it can be tedious. Whether it is because of deadlines, hard software, technical problems, bugs, or even personal goals, this can be very stressful. Not only can this stress lead to a worse state of mental health, which is a very important aspect of people’s personal lives, but also to worse programming.

Many programmers are surprised to hear that lacking rest and a…

An overview of CDF’s and their application in Data Science


Back in May, I took a look at a distribution function that belongs to most statistical distributions called the Probability Density Function, or PDF. The PDF is a very important part of statistical inference, likewise, so is its function brother, the Cumulative Distribution Function, or CDF. If you would like to learn more about PDFs before CDFs, you may read the article I wrote about them here:

I would highly suggest having a decent understanding of the PDF and what it is used for before every even attempting the CDF. This is because CDFs are often far more complicated then…

The real reasons why Julia packages are not well-documented.


While most Data Scientist’s favorite language to work in is likely Python, or less-likely, R, my favorite programming language — period — is Julia. The Julia language is a rather young, Just-In-Time (JIT)- compiled programming language that centers its paradigm around the generic programming concept multiple dispatch. Not only do they use this generic, they apply it everywhere in the language with simply amazing results. If you would like to read an entire article I wrote about Julia and the genius multiple dispatch usage that is in the language, you may view this one here:

A couple of days ago…

A look at the awesome ways that the Julia language made multiple dispatch perfect


Although the Julia programming language is new and not quite popular, at least for now, this does not stop the language from achieving some pretty spectacular feats. The Julia programming language is a lot more unique than many users or viewers even understand, as it resides in its own paradigm. This paradigm is awesome in my subjective opinion, and I have really fell in love with the fantastic type system and parametric polymorphism in the programming language. Julia Computing has dubbed this paradigm

“ The Multiple Dispatch Paradigm”

Okay, so not the most creative naming, but there are so many…

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