Are you looking for a gentle explanation of what Flask is and why Flask is useful for data science practitioners? Well then you are in the right place! In this article, we provide a beginner-friendly explanation of what Flask is, when Flask should be used by data science practitioners, and how to use Flask. This …
Are you looking for an introduction on how to track models using MLflow? Then this is the article for you! In this article we discuss what MLflow model tracking is, why you should use Mlflow model tracking, and how to use MLflow to track your models. After that we will provide examples of how to …
Are you looking for an introduction on how to use MLflow to track the inputs and outputs associated with your scripts? Well then you are in the right place! In the beginning of this article we discuss what MLflow is, why MLflow is useful, and how to use MLflow to track data associated with your scripts. …
Are you looking for a gentle introduction to object oriented programming in Python? Well the you are in the right place! In this article we tell you everything you need to understand what object oriented programming is, why object oriented programming is useful, and how to implement basic object oriented programming in python. This article …
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 …
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 …
