Data Science Playground
Motivation
DAI facilitates data science for enterprises, practitioners, scientists, and students through an extensible data analysis platform together with a powerful hardware equipment. Our expertise encompasses the data science lifecycle from data transformation, predictive modeling, and evaluation to reduce costs and time.
Goals
The Data Science Playground aims to support the identification and specification of research questions. In scientific research projects, solutions for problems in research areas, such as Natural Language Understanding, Recommender Systems, Dialogue Systems (Chatbots), Data Mining on Time Series, Hyperparameter Optimization, Automated Machine Learning, creation and evaluation of domain-specific or contextual embeddings, are developed.
Technology
The Data Science Playground enables the efficient integration and extension of different tools and algorithms, such as:
- cuBLAS, IntelMKL
- MXNet, TensorFlow, Keras, Torch, Scikit-learn, Java Optimization Library
- Google BERT, Zalando Flair, ELMo
- DAI Optimization Toolbox
- Deep Learning, SVM, Time Elastic Learning