300 episodios

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

Data Skeptic Kyle Polich

    • Ciencia

The Data Skeptic Podcast features interviews and discussion of topics related to data science, statistics, machine learning, artificial intelligence and the like, all from the perspective of applying critical thinking and the scientific method to evaluate the veracity of claims and efficacy of approaches.

    Mathematical Models of Ecological Systems

    Mathematical Models of Ecological Systems

    • 36 min
    Adversarial Explanations

    Adversarial Explanations

    Walt Woods joins us to discuss his paper Adversarial Explanations for Understanding Image Classification Decisions and Improved Neural Network Robustness with co-authors Jack Chen and Christof Teuscher.

    • 36 min
    ObjectNet

    ObjectNet

    Andrei Barbu joins us to discuss ObjectNet - a new kind of vision dataset.
    In contrast to ImageNet, ObjectNet seeks to provide images that are more representative of the types of images an autonomous machine is likely to encounter in the real world. Collecting a dataset in this way required careful use of Mechanical Turk to get Turkers to provide a corpus of images that removes some of the bias found in ImageNet.
    http://0xab.com/

    • 38 min
    Visualization and Interpretability

    Visualization and Interpretability

    Enrico Bertini joins us to discuss how data visualization can be used to help make machine learning more interpretable and explainable.
    Find out more about Enrico at http://enrico.bertini.io/.
    More from Enrico with co-host Moritz Stefaner on the Data Stories podcast!

    • 35 min
    Interpretable One Shot Learning

    Interpretable One Shot Learning

    We welcome Su Wang back to Data Skeptic to discuss the paper Distributional modeling on a diet: One-shot word learning from text only.

    • 30 min
    Fooling Computer Vision

    Fooling Computer Vision

    Wiebe van Ranst joins us to talk about a project in which specially designed printed images can fool a computer vision system, preventing it from identifying a person.  Their attack targets the popular YOLO2 pre-trained image recognition model, and thus, is likely to be widely applicable.

    • 25 min

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