Data Science Workshop

We meet to learn more about data science and machine learning by exploring Kaggle competitions.

Kaggle (https://www.kaggle.com) is a platform for predictive modelling and analytics competitions in which statisticians and data miners compete to produce the best models for predicting and describing the datasets uploaded by companies and users.

The competition we are going to discuss is Human Protein Atlas Image Classification.
https://www.kaggle.com/c/human-protein-atlas-image-classification

In this competition, Kagglers will develop models capable of classifying mixed patterns of proteins in microscope images. The Human Protein Atlas will use these models to build a tool integrated with their smart-microscopy system to identify a protein's location(s) from a high-throughput image.
Nature Methods has indicated interest in considering a paper discussing the outcome and approaches of the challenge. The Human Protein Atlas team would like to invite top performing teams to join as co-authors in the writing of this paper.

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On the meetup we will have a presentation by our guest speaker, Natalia Chicherova
https://www.linkedin.com/in/natalia-chicherova-/

Natalia is a PostDoc at Biozentrum, with extensive research experience in 3D visualization.
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What is required:

• Laptop (and charger)
• Gmail account

As we will be using Google Colaboratory, no Python packages installation is required.

Google Colaboratory is a free cloud service hosted by Google to encourage Machine Learning and Artificial Intelligence research. It provides Python 2.7 and 3.6 support, and also a free GPU acceleration (Tesla K80 GPU).

References:
https://colab.research.google.com/notebooks/welcome.ipynb