Viewing profile — jritchie

Location: Edinburgh, UK Remote: Yes Willing to relocate: No Technologies: Machine learning, statistics, deep learning, data science, Python, PyTorch, Numpy, scikit-learn. Résumé/CV…

Location: Edinburgh, UK Remote: Yes Willing to relocate: No Technologies: Machine learning, statistics, deep learning, data science, Python, PyTorch, Numpy, scikit-learn. Résumé/CV…

Location: Edinburgh, UK Remote: Yes Willing to relocate: No Technologies: Machine learning, statistics, deep learning, data science, Python, PyTorch, Numpy, scikit-learn. Résumé/CV…

Probabilistic Programming & Bayesian Methods for Hackers [1] by Cameron Davidson-Pilon is exactly what you want, starting from a computational-first perspective, then introducing t…

> Sure. In 2014. Not in 1969. The LM computer on Apollo 14 had to be updated in flight in order to bypass a faulty abort switch.[1] The patch was applied by radioing the instructio…

Approximately 7,000 residents [1], but over 400,000 employees. [2] [1] http://www.cityoflondon.gov.uk/services/environment-and-plan... [2] http://www.cityoflondon.gov.uk/business/e…

In London, tech does not rule the city. No single industry does. Not even finance. Apart from the City, which is quite literally ruled by the finance industry. [1] [1] https://en.w…

OpenCV 3 supports Python 3[1], but it's not distributed through PyPI. [1] http://opencv.org/opencv-3-0.html

Yes, but the value of the collected data is much reduced if you can't distinguish between legitimate IMSIs and spoofed IMSIs of devices that were never actually there.

Do IMSI catchers have any way of verifying the intercepted IMSIs are legitimate? If not, would it be possible to build a device to flood them with fake/spoofed IMSIs?