The Normal Distribution

Diving deeper into data science I started to brush up my knowledge about math especially statistics. The Mother of all Distributions The normal distribution was formulated by Carl Friedrich Gauß in 18XX and can be implemented in Python like the following : def normal_distribution(x, mu=0, sigma=1): sqrt_two_pi = math.sqrt(2*math.pi) return math.exp(-(x-mu)**2 / 2 / sigma**2)…

Data Science: Cross-Validation

For validating your model you need to split your data into a training and a test data set. More training data means a better model, more test data means better validation. But because the amount of data to train/test the model is limited you have to decide in which ratio of training vs test data…

Introduction to Jupyter Notebook

JuPyteR Do You know the feeling of being already late to a party when encountering something new? But when you actually start telling others about it, You realize that it is not too common sense at all, e.g. Jupyter Notebooks. What is a Jupyter notebook? In my own words: a browser-based document-oriented command line style…

Data Science Datasets: Iris flower data set

The Iris flower data set or Fisher’s Iris data set became a typical test case for many statistical classification techniques in machine learning such as support vector machines. It is sometimes called Anderson’s Iris data set because Edgar Anderson collected the data to quantify the morphological variation of Iris flowers of three related species. This…