In my article My personal road map for learning data science in 2018 I wrote about how I try to tackle the data science knowledge sphere. Due to the fact that 2018 is slowly coming to an end I think it is time for a little wrap up. What are the things I learned about…
What is Feature Scaling? Feature Scaling is an important pre-processing step for some machine learning algorithms. Imagine you have three friends of whom you know the individual weight and height. You would like to deduce Christian’s t-shirt size from David’s and Julia’s by looking at the height and weight. Name Height in m Weight in…
Lesson 2 of the Udacity Course UD120 – Intro to Machine Learning deals with Naive Bayes classification. Mini project For the mini project you should fork https://github.com/udacity/ud120-projects and clone it. It is recommended to install a python 2.7 64bit version because ML is heavy data processing and can easily rip up more than 2GB of…
Questions Data Science tries to answer one of the following questions: Classification -> “Is it A or B?” Clustering -> “Are there groups which belong together?” Regression -> “How will it develop in the future?” Association -> “What is happening very often together?” There are two ways to tackle these problem domains with machine learning:…
I got confused by all the buzzwords: data science, machine learning, deep learning, neural nets, artificial intelligence, big data, and so on and so on. As an engineer I like to put some structure to the chaos. Inspired by Roadmap: How to Learn Machine Learning in 6 Months and Tetiana Ivanova – How to become…