If Leslie had hit Portugal as hurricane, it would have been the first time in recorded history that Europe had seen the landfall of a hurricane. As it happened, Leslie was officially a hurricane until re-classified as a post-tropical cyclone at 1800 GMT by the National Hurricane Centre in Florida. Leslie made landfall about four hours later, near Coimbra, halfway between the cities of Lisbon and Porto, Portugal. Winds were recorded as 122km per hour in Coimbra but were reportedly as high as 176 km/h at Figueira da Foz. Local media reported many trees down and electricity supplies cut to 15,000 households.
Matthew Braga is the senior technology reporter for CBC News, where he covers stories about how data is collected, used, and shared. If you have a tip, you can contact this reporter securely using Signal or WhatsApp at 1 416 316 4872, or via email at email@example.com. For particularly sensitive messages or documents, consider using Secure Drop, an anonymous, confidential system for sharing encrypted information with CBC News.
In this talk we will present some techniques that we use on a day to day basis in our research, where we combine our internet-wide data scanning and acquisition platform with ML/Data science techniques which allows us to find things faster or extract results in a more automated way. We will focus on practical cases and examples that even our audience at home will be able to use if they want. A couple of examples we will look at is how to classify images such as VNC screenshots, we will look at network scans and using machine learning to classify them and also the use of natural language processing to analyze CVEs. We will also talk a bit about a data analysis and classification pipeline architecture, we will look at the different technologies and what they do and how they can be used. We will start by giving a very brief entry to the data science world and talk about: Technologies Techniques How these relate to infosec Algorithms and how they can be used How people can come into the world of data and machine learning Data visualization techniques and what are the best choices for different types of data A couple of examples we will look at is how to classify images such as VNC or x11 screenshots, OCR, we will look at network scans and using machine learning to classify them and also the use of natural language processing to analyze CVEs.
Lisbon, Portugal - Artificial intelligence, or AI, has become a commonplace technology, helping researchers make improvements to computerised tasks such as speech recognition and robotics. Machine learning, a branch of AI, allows the flood of data collected from devices to be organised, analysed and visualised in an intelligent fashion. These powerful insights make products such as fitness trackers and climate sensors more appealing. But as the technology evolves, experts are cautioning about the potential threats AI could pose in the future. "AI could be used to deal with particular issues around privacy and surveillance and things like this," Antoine Blondeau, chief executive of Sentient Technologies, told Al Jazeera at the Web Summit in Lisbon.
From July 20th to July 28th 2016, I had the opportunity of attending the 6th Lisbon Machine Learning School. The Lisbon Machine Learning School (LxMLS) is an annual event that brings together researchers and graduate students in the fields of NLP and Computational Linguistics, computer scientists with an interest in statistics and ML, and industry practitioners with a desire for a more in-depth understanding. Participants had a chance to join workshops and labs, where they got hands-on experience with building and exploring state-of-the-art deep learning models, as well as to attend talks and speeches by prominent deep learning and NLP researchers from a variety of academic and industrial organisations. You can find the entire programme here. In this blog post, I am going to share some of the highlights, key insights and takeaways of the summer school.