Don’t mock me, but for some reason whenever I see or hear the word “git” the song “Get Down Tonight” by KC & The Sunshine Band automatically plays in my head. Am I the only one? Most likely. Within this article I will be going over Git for Mac users, from set up to functionality. Let’s get started.
I used the site https://git-scm.com/download/mac to first understand how to download git for my Mac book. I already had Homebrew on my computer, therefore, all I did was go into my terminal and type:
brew install git
The interview process can be a very intimidating thing (trust me, I’m in the middle of it right now.) When reading job descriptions they can be so vague that it is tough to know where to even begin. In this blog post we will go over how to search for a job, effective networking, and possible interview questions/answers to prepare you for your first interview.
The first step in beginning an effective job search is accepting to yourself that the search will not be easy. A job search is a full time commitment, if your plan is to simply apply to a couple of job posts via LinkedIn, I would think again. The goal is to show you are knowledgable in the field of Data. …
There are many popular processes for a data scientist to go through in order to complete their work, one of the most popular in the field at this time is a strategy classed OSEMN (rhymes with awesome). Today we will cover the five steps of OSEMN and why it is such a useful tool for data scientists. For this blog post we will focus on Linear Regression as our type of model.
Obtaining data can be performed in a variety of ways. Depending on what company you are working for they may provide the data for you, if not you will most likely need to web scrape, use an API, or be familiar with SQL. Once the data is obtained, it is important to take a look at what you have acquired and become familiar with your dataset. …
When discussing data visualizations it can be overwhelming deciding what type of chart to use where. Am I presenting the data clearly? Does the it make sense to the customer? Is it aesthetically pleasing? Here we are going to go over some of the most common types of data visualizations and how to use them in your notebook.
For all below graphs I am modeling seaborn. Coding information can be found at seaborn.pydata.org
import seaborn as sns
STEP TWO: Choose your visualization
Barplots use bars to show comparative data. Barplots can be created horizontally or vertically. Best practice is that a horizontal barplot would be used with longer bars whereas a vertical barplot can be used for positive or negative data. With the code below I created a horizontal bar graph comparing movie directors and the domestic gross their movies brought in. …
It’s 2020 and so much has changed, while we aren’t quite yet living like the Jetson’s with our flying cars, alot of progress has been made. Look around you: from driverless cars, using face recognition to unlock your smart phone, and automatic facebook tags. Image classification is in full use. We even use image classification to identify sicknesses such as pneumonia or cancer. How do computers do this? The answer lies in Convolutional Neural Networks or CNNs.
While conducting a job search for “Data Scientist” or “Data Analyst” three letters often pop up in the job description section. These three letters are SQL also known as Structured Query Language. This is a process that is used to extract and organize data that is stored in a relational database. When hearing the term relational database think of one or more data tables that share common columns. For example, below we have two tables “stocks” and “news” which contain a similar column of date.
Just because we are working with numbers and code doesn’t mean we need to have a boring Jupyter notebook. In this blog we will go over different ways to spice up your notebook and make it visually pleasing for your readers. Ready? Let’s get started.
Here’s how it looks