Let's discover the fascinating myths of big data & machine learning together.

Let's discover the fascinating myths of big data & machine learning together

About me ...

I am fascinated by big data technology and machine learning algorithms, and building practicable high-quality solutions for real world problems. I learn daily to deepen my knowledge and continuously expand the boundary of ideas I can comprehend and interrelate. I seek to bridge the gap between implementation technologies and theoretical algorithms to build practical high-quality solutions for real world problems.

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I write blog posts to share and validate my way of understanding, and to help others understand. I try to illustrate complex concepts in an easily graspable and comprehensible way, starting with a small concrete example. I also develop and share my own thoughts about approaches and their applications.

Once upon a time ... a short story about how I came to be

I recall being in university in my first semester of Computer Science, listening to my lecturer on Linear Algebra. The previous year, I was in High School and gifted with a wonderful Maths teacher. He was aiming to teach us a real comprehension of the concepts and correlations, rather than the dull repetition of learned procedures. I didn't know at the time, but it was just the way I needed to be taught - that's why I sucked it up like a dried-out sponge. For me, it all made sense and fell into place. I finished the final exam with all possible points, handing in 30 minutes early. I do not take credit for this - it was the result of a synthesis of a great teacher and an eager student.

However, listening to this professor at university I came to doubt my abilities to follow him. He didn't intend to explain anything - he was simply copying definitions from the text book to the blackboard, while reading them out loud. Literally more abstract indices - which he most often confused himself - than words describing their usefulness. I decided quickly that it was waste of time to attend this lecture, and started to study online with a wonderful course published by the Stanford University. The very first thing the lecturer did, was to write a small matrix to the blackboard, and then explain the definition by walking through a very simple example. I received the best possible grade in the exam, while many had failed.

I believe that there is always a simple and graspable way to explain even complex concepts. I also believe that knowledge has compound-interest: As one acquires more, one can understand new correlations faster and therefore, learn more. That's why I am eager to learn new things and explain them to others in a simple and understandable way.