I completed my postgraduate degree in Data Mining and Information Retrieval at the University of East Anglia in UK.
I am trying to challenge the old saying, "Jack of all trades, master of none". I have about 10 years experience in Software Development. In previous lives I used to work as an Information Security Consultant and Presales Manager. I also have been volunteering in Global Voices Online (GVO) since 2007, and currently I am local ambassador of the Open Knowledge Foundation (OKFN) in Egypt. Words like Machine Learning, Natural Language Processing, Open Data, Government 2.0, Data Visualisation, Data Journalism, New Media, Startups, Sociology and Philosophy are like music to my ears, whereas I do not like the term Big Data.
My C.V. via Linkedin
This is your guide to mastering the efficient use of D3.js in professional-standard data visualization projects.
I co-authored the book with Rayna Stamboliyska. You can order it from any of the following:
List of some of my software projects and micro-projects on github:
In today’s world, millions of web links are being shared every day in emails or on social media web sites. Thus, there is a number of contexts in which it is important to have an efficient and reliable way to classify a web-page by its Uniform Resource Locators (URLs), without the need to visit the page itself. For example, a social media website may need to quickly identify status updates linking to malicious websites to block them. Additionally, they can use the classification results in marketing researches to predict users’ preferences and interests. Thus, the target of this research is to be able to classify web pages using their URLs only.
New! Throughout the course of your career, you may need to quantify the effect of changes you make to a product or service. These change can be the introduction of a new design to a website, the creation of a new medicine, or even choosing one football player to take a penalty kick for your team over another in the World Cup final. The way we quantify these changes is usually via A/B experiments. Traditionally, the frequentist approach prevails. However, Bayesian approach is that it is more intuitive and easy to explain to your stakeholders. You can communicate to them — from day one — the belief you have reached about your samples’ differences. Additionally, you can make use of prior knowledge you have about your website visitors and plug it into your analysis to reach a quicker conclusion.
Slides presented to the students of Transparency International's School of Integrity in Tunisia. The presentation discusses the role of Open Data and how it is used for more transparency and better governance.
List of places online where I write every now and then. I normally mix between social, technical, political and other miscellaneous topics.
I am going to write and upload machine learning and text mining related tutorials; all in Jupyter notebooks. Jupyter (formerly IPython) notebooks allows me to write Python code, inline with explanation and graphs. These notebooks are hosted on githib, so feel free to use the code there, or fork and add (or fix) anything, if you want.