Every profession has their unique toolbox, full of items that are essential to their work. Painters have their brushes and canvas. Bakers have mixers, pans, and ovens. Trades workers have actual toolboxes. And those in a more corporate environment will have a suite of hardware and software necessary to complete…


Clustering is one of the most popular types of unsupervised machine learning. Clustering techniques allow us to group data objects into similar classes in such a way that items within a group share similar characteristics, while items in different groups are not similar at all.

cluster analysis 101

It could be said that…


Doing more work with less effort is the name of the game in coding. For data scientists, this is a huge advantage to using tools like Python to assist with extracting as much information from data as possible in an efficient way.

Data exploration is one of the early steps…


The comparison between the way things are and the way things ought to be is one that is made frequently. Good ice cream should be inexpensive, if not a free, public good, but oftentimes it is quite expensive. Exercise should be something we all strive for — it makes us…


Many things in life come in a variety of shapes, sizes, flavors, etc. It is this variety that is said to be “the spice of life”. Unfortunately, data scientists often have to save the variety for after hours and get the data they are working with to become rather similar.

credit to Analytics Vidhya


“SQL is an important tool for any data scientist” — is my entry for the understatement of the year.

As information jockeys, data scientists use SQL to query the data they will need for analysis from established databases. Depending on the demands of your position as a data scientist, you…


“There are two kinds of people in this world…”

Are words we’ve all heard before, typically from an elder relative trying to make sense of some bigger picture for you. As cliche as the statement is, demographic information — identifiers which tell us something about the members of a population…


Once one has a good understanding of the data they have to work with, they next need to decide what they aim to answer with this information. Understanding the problem at hand is part of the Business Understanding step in the Data Science Process.

The Data Science Process

A business question with a data…


It is widely reported that over 80% of a data scientist’s time is spent cleaning and engineering data. Great effort is put into preparing the information that will feed a data scientist’s models. …


Why it is important to know what your end goal is…

When I set out on a two month journey to complete my capstone project for Flatiron School, effectively ending the first chapter of my story to become a data scientist, I knew that I wanted to have something more…

Zach Zazueta

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