In this article we discuss using unit tests for data science projects. Specifically, we talk about using the pytest module in python to implement unit tests for data science projects. We will discuss what unit tests are, how they are useful, and how to set them up using pytest. This article was created as part …
In the previous step of this case study, we explored our data in an ad hoc fashion using Jupyter notebooks. Now it is time to get to work on the code that will be used to prepare our data and train our model. Before we start coding, we will set up a Python package so …
What is a python init file? In this article we tell you everything you need to know about a Python init file, otherwise known as an __init__.py file. We discuss what the Python init file is used for, what needs to be put in a Python init file, and whether all Python packages need a …
Now that we have set up our environment, we can dive into the data by performing some basic data quality checks. This post is going to be focused more on the summarizing types of data quality checks that should be implemented for simple tabular data rather than writing the code to implement these checks. As …
In the previous step of this case study, we set up a git repository to version control our code. Now we will set up a package manager to manage our Python environment. This will give us fine grained control over the package versions we use and allow us to easily navigate between different environments that …
One of the first steps you should take when starting a new data science project is setting up a new repository to version control your code. For the sake of this case study, we will be using git to version control our code and GitHub to host a version of our git repository online. In the following article we will …
In this article we provide a beginner-friendly explanation of how to use git to version control your code. We cover all of the concepts necessary to understand how git works and how to use it. First, we give a high level overview of version control and common features of version control systems. After that, we …
Are you wondering whether you need to use version control software for your data science projects? In this article, we go over all the benefits of using version control software for data science projects. In this post we focus on the importance of version controlling your code, as opposed to version controlling other aspects of …
Are you looking for a step-by-step guide on how to create a data science project to enhance your portfolio? Well then you are in the right place! Purpose of this case study In this case study we will focus on the engineering skills that go into building and deploying machine learning models using code that …