wednesday-14:35 Session List
AI Intentions and Code Completion
Vasily Korf
Artificial Intelligence, Code-Review, IDEs/ Jupyter, PythonDatalore supports intentions – code suggestions based on what you’ve just written.
Automating feature engineering for supervised learning? Methods, open-source tools and prospects.
Thorben Jensen
Artificial Intelligence, Algorithms, Data Science, Machine Learning, Data EngineeringHow to automate the labor-intensive task of feature engineering for Machine Learning? This talk gives an overview on methods, presents open-source libraries for Python, and compares their performance.
How MicroPython went into space
Christine Spindler
MicrocontrollersMicroPython used in space as an On Board Control Procedure (OBCP) engine
Julia for Python
Simon Danisch
Data Science, Infrastructure, IDEs/ Jupyter, Parallel ProgrammingJulia is a new Language, that is fast, high level, dynamic and optimized for Data Science. Learn about Julia's strengths and how you can integrate it in your Python workflow!
Why you should (not) train your own BERT model for different languages or domains
Marianne Stecklina
Artificial Intelligence, Deep Learning, Data Science, Natural Language Processing, Machine Learning, ScienceLanguage models like BERT can capture general language knowledge and transfer it to new data and tasks. However, applying a pre-trained BERT to non-English text has limitations. Is training from scratch a good (and feasible) way to overcome them?
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