Past Events

  • Dealing with Imbalanced Data - Adrian Spataru

    Imbalanced data is a common problem in lots of domains, such as Fraud detection, Disease detection etc. In this talk, we will cover different methods for dealing with such problems. For example: SMOTE, ADASYN, Feature Learning and more.

  • Transfer Learning Overview & Finetuning Tutorial - Adrian Spataru

    Transfer learning is a machine learning method where a model trained for a domain is reused as the starting point for a model on a related domain. In this presentation, we explore different transfer learning techniques and explore the different type of pretrained models (Image, NLP) at our disposal. Furthermore, there will be a tutorial on finetuning for image recognition tasks.

    Slides Code
  • Hawkes Processes Tutorial - Tiago Santos

    Hawkes processes are a stochastic method for modeling discrete, inter-dependent events over continuous time. Problems like these can be found in a lot of domains. In finance, an event can represent a transaction on the stock market that influences future prices. In geophysics, an event can be an earthquake that is indicative of other earthquakes in the vicinity.

  • Reinforcement Learning & Google DeepMind Talk - Anand Subramoney

    Reinforcement Learning Tutorial - Talk about the two main classes of learning algorithms (value-based learning and policy-based learning) with examples

    Google DeepMind Talk - Talk about following deep mind papers: • Mnih, V. et al. Human-level control through deep reinforcement learning. Nature 518, 529–533 (2015). • Mnih, V. et al. Asynchronous Methods for Deep Reinforcement Learning. arXiv:1602.01783 [cs] (2016).

    Slides Files
  • Dockerize Your Data Science Environment - Florian Geigl

    A Presentation on the open source Docker container used at Detego for all data science related tasks, followed by a live demo and some best practices.

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  • Predicting Instagram Likes - Adrian Spataru

    Can we predict likes in online social networks? What makes a post "attractive"? In this presentation, we will try to answer these questions.

  • Machine Learning 101 with Scikit-Learn - Adrian Spataru

    Understand the basics of Machine Learning and build your first model.