In recent years, “Machine Learning” has evolved into a buzzword that is used for describing all sorts of modeling. When studying Machine Learning it is important to get acquainted with all the different categories below the famous umbrella term. First, Machine Learning can be broken down into two simple categories, “Supervised Learning” and “Unsupervised Learning”. I will only focus on the Supervised Learning subset in this article. Supervised Learning is a class of machine learning that can “learn” a task through labeled training data. The labeled data is what makes a difference between Supervised Learning and Unsupervised learning, Unsupervised Learning…

Data Science can be an intimating world to jump into. That is why below I have listed some helpful resources to help someone get started. While Data Science is a challenge, there are countless sources around the internet, in your local bookstores, or easily purchased that can help someone break into the industry.

Non-Technical Books

Thinking Fast and Slow by Daniel Kahneman

This international bestseller authored by noted economist and psychologist Daniel Kahneman takes the readers on a fascinating journey by dissecting the mind and goes onto explain two distinct systems that affect our way of thinking and making choices. Of these…

When working with mass amounts of data it is impossible to get an understanding of the data by simply looking at the values. That is why as a data scientist it is important to be able to properly visualize the data. There are many different ways in Python to effectively visualize data, in this article I will summarize a few of them.


First, and probably the easiest way for us to visual data is by using the Python library Matplotlib. When beginning with Matplotlib it is important to understand the graphic below.

This graphic shows the typical structure of…

What happens when one of the oldest traditions of mankind meets today’s most powerful tools? In 2001, Bill Benter, a professional gambler and mathematician, put this question to the test.

Horseracing, or the “Sport of Kings”, dates back as far as 4500 BC, with the nomadic tribesmen of Central Asia, who were the first to domesticate horses. Since then, most eras of our history have instances of horse racing; whether it was the Ancient Greeks, English Knights, or Native Americans, they all have instances of racing horses. There are many important variables that make a successful racehorse, a few examples…

Alex Zieky

Financial professional with experience in data acquisition, data modeling, statistical analysis, machine learning, deep learning, and NLP.

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