Machine Learning and Neural Networks

Our Approach

From Business Goals to Mathematical Models

Due to our long-standing experience in scientific research the development and implementation of mathematical and physical models is one of our strengths. Our work is tailored to the requirements and demands of your company so that you can rely on predictions and forecasts of the corresponding simulation results for future decisions and take choose best option.

Use mathematical models to make better decisions for your company - we develop the right tools for you!

Use mathematical models to make better decisions for your company - we develop the right tools for you!

The basic idea behind the mathematical modelling of business questions is to calculate predictions for your company, which show the outcome of certain decisions or help to forecast certain trends. We apply diverse algorithms, scientific laws of nature, statistics, neuronal networks, machine learning and much more. Examples for typical questions that can be treated with such methods are:

  • What will be the result/consequence of a certain decision?
  • What should be do next?
  • How should we proceed to exploit probabilities in our favour?

The application of mathematical models is of big avail especially for cost-intensive decisions, because serious consequences can usually be determined beforehand with relatively low efforts.

Approach and Models

We clarify in a personal discussion which model suits your problem best. The possible solution relies heavily on the available data - if one knows, how a systems is working, usually physical laws based on classical models can be applied. Is this not the case or if only partial information is available, models based on data are the method of choice.

Among others we use deep learning optimisation routines to calculate predictions for your company.

Among others we use deep learning optimisation routines to calculate predictions for your company.

A very efficient method is the so called deep learning - this is the general term for learning algorithms and optimisation methods of neuronal networks, which nowadays are very successfully employed in automotive cars, photo and image recognition, in the financial world for risk or stock price forecasting, in biology and medicine or for the recognition of anomalies in the IT sector.

Use our enthusiasm for such possibilities in mathematics and physics to get the best out of your company and to be able to make decisions based on mathematical facts!

Final Product

How the mathematical models are integrated into your infrastructure in the end depends heavily on your requirements and condition. A few possible examples are listet here:

  • MXnet for deep learning algorithms
  • Fortran code with executables
  • Standalone Matlab application
  • Interactive CDF Mathematica-files with graphical user interface
  • Cloud APIs

Big Data Example

A simple example for the business-related information that can be extracted from a given amount of data are the taxis in New York. Every month the collected taxi data (time and place of pickup, distance, fare, number of guests, etc.) ist published on a website. The data volume of one year is quickly more than 20 GB and it is not possible to simply open or process such an amount of data in Excel or another conventional office program (catchword Big Data). Nevertheless, with the appropriate tools such gigantic amounts of data can still be processed easily and already simple statistical models allow to make important strategic company decisions. In the following animation the result of a Matlab simulation is depicted, where the taxi data of one day has been evaluated.

Animation of taxi pickup data in New York within one day. Copyright 2016 The MathWorks, Inc.

Animation of taxi pickup data in New York within one day. Copyright 2016 The MathWorks, Inc.

Already with this first and simple result we can draw conclusions at which particular time a taxi company will need the most drivers and at which place they should be positioned. If we apply further statistical analysis we learn for example that at 19:00 the tips are highest, which driving distance is most common or at which time of the day the most group taxis will be needed. The next step would be to apply corresponding forecast models, so that the right taxis can be placed at the right position and time with the calculated probabilities - this optimisation could be a crucial advantage compared to other competitors.

No matter what kind of data you have in your company, we help you with the evaluation and establish mathematical models and analyses tailored to your requirements.

No matter what kind of data you have in your company, we help you with the evaluation and establish mathematical models and analyses tailored to your requirements.

Simulation and modelling

We create mathematical solutions and simulation models tailored to your requirements.

Visualisation and evaluation

Analyses, diagrams and evaluations on demand, helping you with your decisions and solving your problems.

Mathematica, Wolfram|Alpha & Multiparadigm Data Science

State of the Art algorithms for all possible areas and built-in knowledge from Wolfram|Alpha for better and faster results.

Integrated to your infrastructure

The final results are passed on to your infrastructure and can be processed with the tools you are familiar with, e.g. Excel, Power BI, Tableau, Matlab, Mathematica etc.

Machine Learning & Data Science

Use the possibilities of machine learning that go far beyond standard Business Intelligence tools.

Secure

Your data is processed locally and never leaves your network.

Machine Learning and Neural Networks

If you would like to find out more, please get in touch.

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About us

We are an independent consulting company for Business Intelligence and develop individual Data Science solutions.

Address in Sweden

Månstavägen 45
79690 Älvdalen
Sweden
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Contact for Austria, Germany and Switzerland

Dr. Andreas Trügler: andreas.truegler@atseda.com