AIQC simplifies data preparation and parameter tuning for batches of deep learning models without an expensive cloud backend.

It empowers researchers by reducing the programming and data science know-how required to integrate machine learning into their research. It makes machine learning less of a black box by reproducibly recording experiments in a file-based database that requires no configuration.

Malte Pietsch delivers this keynote on “Transfer Learning – Entering a new era in NLP” at PyData Warsaw 2019

Transfer learning has been changing the NLP landscape tremendously since the release of BERT one year ago. Transformers of all kinds have emerged, dominate most research leaderboards and have made their way into industrial applications. In this talk we will dissect the paradigm of transfer learning and its effects on pipelines, modelling and the engineers mindset.