The interquartile range method is my preferred method to identify outliers because the method itself is easy to understand and I created two functions that can be applied to every pandas DataFrame to create a little PDF report of all numeric features in your dataset. The interquartile range method uses the 5-th and 95-percentile to … Read more
Pearson Correlation OLS Regression Results OLS Regression Plots
When I start a new data analysis it helps me to have a fixed plan that I know how to execute. Therefore I do not get stuck by all the possibilities that a new dataset offers. In this article I show you my 3 steps that I do with every new dataset along with other … Read more
In this article I show you how to create a basic classifier for the Kaggle Titanic competition. In the first part of this article we start with the simplest approach and build a solid foundation for more complex machine learning models that include cross validation to increase the generalization of our model. In the second … Read more
In this second article about the Kaggle Titanic competition we prepare the dataset to get the most out of our machine learning models. Therefore we clean the training and test dataset and also do some quite interesting preprocessing steps. In the first article we already did the data analysis of the titanic dataset. You find … Read more
This article is for you if you use Jupyter on your local pc and: still upload your latest changes of a program manually to your GitHub account or have no version control of your files at all because in this article I show you how to use GitHub as version control out of your Jupyter … Read more
Today we start the Titanic Kaggle competition. Our objective is to build a classifier that predicts which passengers of the Titanic survived.If you want a detailed description of the Titanic Kaggle competition, you find all information on the Kaggle website. I separated the process of building the classifier in the following tasks: Today we take … Read more
