Welcome to 37 Steps

Be ready for Adventures in Data Analysis.

Ask questions.
Make observations.
Analyze and understand.
Learn with passion.
Draw conclusions.

We are fascinated by the human abilities to wonder, discover, experiment, learn and reflect. At the same time, we are fascinated by the abilities to discard, forget, change and grow. We think consciousness is an essential aspect of all this.

Pattern Recognition is both an art and a discipline, where we learn from data in an intelligent way. We observe both nature and humans and imitate their learning principles on a computer.

Inspiration comes from both sides. The understanding of pattern recognition methods inspires us to think about humans and their relations with each other.  On the other hand, the understanding of living organisms in their environments allows us to develop or tune specific approaches for the artificial learning.

We are highly experienced both in theory and application of pattern recognition tools. We want to share our knowledge and provide understanding to a wide audience.

You will love our tools and approaches because they are well explained and easily coded.

The goal of this site

In our fast developing technology, we are currently flooded with data. In meantime, it has become increasingly more and more important to know the data, that is, to understand their relations and learn from them in a meaningful way. The reason is simple – no one can understand the complexity of relations any longer unless meaningful patterns are extracted or discovered, while intelligent methods are applied.

Pattern recognition tools are a perfect solution for such needs. They can be applied to any data when understanding or learning are necessary.

The goal of this initiative is twofold:

  1. First, to explain and teach you the practical pattern recognition approaches (learning).
  2. Secondly, to provide services which analyze your data (results).

We, therefore, offer explanations, reports, tutorials, data, tools and services in the area of pattern recognition.

  • Pattern recognition introduction
  • Feature-based approaches
  • Kernel-based approaches
  • Dissimilarity-based approaches
  • Real world examples
  • Tutorials and learning options
  • Services

If you are curious why we chose the name of 37 Steps, the answer is here.

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