In this code snippet, we look at how to edit axis and legend labels in seaborn. While this is a very basic task, it is one I find myself often searching the internet for. To give you (and me) a shortcut to a code example, I created this little post.
In classification problems, we often want to assess the quality of our model beyond a simple metric like the models accuracy, especially if we have many different classes or they are of different importance to us. In this short article, I show you a more intuitive way to present the quality of your classification model - a color coded Confusion Matrix.
One of the top communities for data science is the online-community of kaggle.com. There are tutorials, discussions, datasets and online competitions on this website. Beyond that, kaggle is one of the most important tools of the open source data science community. Not only through the sharing of code and datasets, but mostly by crowd sourcing data science projects through competitions. Even top notch tech companies have leveraged the power of these competitions and reward participants with high prizes (at the time of writing, the highest being $100,000 offered by Jane Street Group).
