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Viral Tweets: a K-Nearest Neighbor Algorithm Part I

In my latest Codecademy project I was assigned to use Python and sklearn’s KNeighbor algorithm to find the attributes that could potential make a tweet go viral. But first a quick rundown on what is K nearest-Neighbor (KNN). KNN is a great way to classify data. KNN takes in data points, and uniquely categorizes them […]

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Viral Tweets: a Naive-Bayes Algorithm-Story Part II

In the second part of my Codecademy project I was assigned to build an Naive-Bayes algorithm to tell whether a tweet someone wrote originated from either NYC, London, or Paris. Not gonna lie that sounds hella cool, but before I carry on what is a Naive-Bayes algorithm? NBA is a popular classification machine learning algorithm […]

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KMeans Models & Masculinity: A data science story.

In my latest codecademy project I used a survey from FiveThirtyEight on What Do Men Think It Means To Be A Man? The whole article is worth a read, and I think these sort of surveys are great for K-Means cluster analysis. After reviewing the survey I decided to look at one questions in particular: […]

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Cleaning Data with [r]egex

Any important part of working with data is the ability to manipulate it into useful data. Whether that’s cleaning it up, or transforming the table so it can be easier to use. Cleaning data is usually the first step in any data science project, and can be where you spend most of your time. How […]

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Biodiversity: A Data Science Point of View

Recently I was able to analyze some data from the National Parks Service on endangered species. This project had me using key functions of python to reshape data and plot graphs. Like any good data scientist being able to extract meaning from data is paramount, and as my quest to share knowledge grows, I hope […]

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Netflix & Plot: Visualizing Stocks with Seaborn, Matplotlib, and Python

Most practitioners don’t like to mention it, but I’m just following the money, and nothing takes to data science like money. The well-off may like to preach the story of the self made man, but nothing is more adverse to risk-taking than established fortunes, and what is data science if not the most un-risky understanding […]

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Data Science: Kiva & Seaborn

In my latest article on data science I’ll go deep into using Seaborn. A visual module in python that charts different graphs for us. For my data-set I’m going to use the micro-loan nonprofit group Kiva to get a peek into how loans are distributed. If you want to follow along or find some other […]

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Objectification of Python Objects, and the Rise of Classes

Python objects are an essential tool when programming. It can bring real dynamics to what you are trying to achieve, and broaden the creative scope one can accomplish when writing a script. So I wanted to explain some of the basics, and lay out the case for why coding in python can be one of […]

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Objectification of Python Objects and Their Inheritance

In my last article I explained how to set up a Python class with some basic parameters using the dunder methods, and a custom function to handle a student’s grade average. Here I want to address the capabilities of Python class inheritance. Let’s say later on I want to start organizing the schools in my […]

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