Data science & machine learning

Consulting

Not every problem can be solved by machine learning. Conventional software development often helps to reach your goal more effectively. But for you, which option is the better one? Should you use the traditional way to solve your problem, or should you prefer machine learning? We can help you to find out.

Data mining and exploration

In order to obtain insights into your data, we conduct an exploratory analysis. As a result, we discover patterns or correlations and visualize the findings. If you do not have sufficient data, we can aggregate them from the web.

Modeling

Our data science team has experience with a broad spectrum of statistical and machine learning models. We identify and test different models that might be suitable for your problem. We will explain the advantages and disadvantages of the different approaches and advise you in your decision-making.

Implementation and integration

We work with various open source machine learning (ML) frameworks, such as PyTorch, Tensorflow, Keras, Numpy, Scipy, Edward, PyMC3, Scikit-Learn, etc. ML models can be deployed via Docker containers. Integration can be done via a RESTful API or a front-end application.

Cloud

ML models can be deployed as cloud applications (AWS, Azure, Google Cloud Computing).

Areas of expertise

Our data science team is experienced in the following domains:

Natural language processing (NLP)

Information extraction
Questions & answers
Chatbots

Computer vision (CV)

Image classification
Object recognition
Object segmentation

Predictive analytics

Customer segmentation
Recommendation systems
Fraud detection
Anomaly detection
Predictive maintenance
Time series predictions

Workshops and tutorials

We give practical workshops and training in the fields of data science, machine learning and deep learning:

Learning the concepts of data science
Hands-on tutorials on machine learning with Python (Numpy, Pandas, Scikit-Learn)
Hands-on tutorials on deep learning with PyTorch or Tensorflow in different architectures and for different application fields:
- Natural language processing
- Computer vision
- Predictive analytics
- Feedforward neural networks
- Convolutional neural networks
- Recurrent neural networks (LSTM, GRU)

Data science and machine learning