Data Science Overview

Data Science tries to answer on 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?”

SQL-Basics: Create – Read – Update – Delete

This episode is about the basic statements needed to create, read, update and delete data in a database system.

Let’s assume we work as a data scientist for Knight Industries.  We want to help the Foundation of Law and Government to keep track of our operatives.

We decide to use a classic relational database management system or RDBMS. In order to explore Database Management Systems we can either install one locally or we can use an online tool like SQLFiddle.

To interact with RDBMS we use SQL – the Structured Query Language.

As the name says SQL (speak either S-Q-L or Sequel) is used to write structured queries. Think of “conversations” when You think of “queries”.

So, let’s fire up SQLFiddle. Continue reading “SQL-Basics: Create – Read – Update – Delete”

My personal road map for learning data science in 2018

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 a Data Scientist in 6 months a hacker’s approach to career planning I build my own learning road map for this year: Continue reading “My personal road map for learning data science in 2018”