Academic Ranking of World Universities | ARWU | First World University Ranking | Shanghai Ranking Exploration de données Un article de Wikipédia, l'encyclopédie libre. Vous lisez un « bon article ». L'utilisation industrielle ou opérationnelle de ce savoir dans le monde professionnel permet de résoudre des problèmes très divers, allant de la gestion de la relation client à la maintenance préventive, en passant par la détection de fraudes ou encore l'optimisation de sites web. C'est aussi le mode de travail du journalisme de données[1]. L'exploration de données[2] fait suite, dans l'escalade de l'exploitation des données de l'entreprise, à l'informatique décisionnelle. Histoire[modifier | modifier le code] Collecter les données, les analyser et les présenter au client. De 1919 à 1925, Ronald Fisher met au point l'analyse de la variance comme outil pour son projet d'inférence statistique médicale. L'arrivée progressive des micro-ordinateurs permet de généraliser facilement ces méthodes bayésiennes sans grever les coûts. Applications industrielles[modifier | modifier le code]
Pseudonymization vs. Anonymization and How They Help With GDPR January 5, 2017 Pseudonymization and Anonymization are two distinct terms that are often confused in the data security world. With the advent of GDPR, it is important to understand the difference, since anonymized data and pseudonymized data fall under very different categories in the regulation. Pseudonymization and Anonymization are different in one key aspect. You can think about it in terms of authors. In practice, let’s look at tokenization. Here, with the pseudonymized data, we may not know the identity of the data subject, but we can correlate entries with specific subjects (records 1 and 7 reference the same person, records 2 and 5 reference the same person, records 3 and 4 reference the same person). Pseudonymization is a method to substitute identifiable data with a reversible, consistent value. With Anonymization, we must also be concerned about “indirect re-identification”. “50 people went to this coffee shop every morning.” “100 people got money from this ATM every Friday.”
How to Think Like a Computer Scientist Learning with Python by Allen Downey, Jeff Elkner and Chris Meyers. This book is now available for sale at Lulu.com. How to Think... is an introduction to programming using Python, one of the best languages for beginners. How to Think... is a Free Book available under the GNU Free Documentation License. Please send suggestions, corrections and comments about the book to feedback{at}thinkpython{dot}com. Download The book is available in a variety of electronic formats: Precompiled copies of the book are available in PDF and Postscript . Translations Here are some translations of the book into other (natural) languages: Spanish translation by Gregorio Inda. Other Free Books by Allen Downey are available from Green Tea Press. If you are using this book and would like to make a contribution to support my work, please consider making a donation toward my web hosting bill by clicking on the icon below.
the museum of science, art and human perception * Algorithm (Photography) - Definition - Lexicon & Encyclopedia AlgorithmAn algorithm describes a set procedure to complete a task in computing. It comprises the actions needed to complete a specific task, or for solving a specific problem. [>>>] How do algorithms listen to music?From copyright monitoring and cover song detection to classifications of all kinds (genre, style, mood, key, year, epoch), all the way to the music curation war waged by the music streaming titans, ... [>>>] Demosaicing Algorithms: Color FilteringPrev NEXTA more economical and practical way to record the primary colors is to permanently place a filter called a color filter array over each individual photosite. [>>>] The one clear thing about how the Instagram ~[⇑] works is that posts with high engagement rates show up first on users' feeds. [>>>] ~[⇑]s[edit]Simple interpolation[edit]These ~[⇑]s are examples of multivariate interpolation on a uniform grid, using relatively straightforward mathematical operations on nearby instances of the same color component. [>>>]
A Course in Machine Learning What’s the “problem” with MOOCs? « EdTechDev In case the quotes didn’t clue you in, this post doesn’t argue against massive open online courses (MOOCs) such as the ones offered by Udacity, Coursera, and edX. I think they are very worthy ventures and will serve to progress our system of higher education. I do however agree with some criticisms of these courses, and that there is room for much more progress. I propose an alternative model for such massive open online learning experiences, or MOOLEs, that focuses on solving “problems,” but first, here’s a sampling of some of the criticisms of MOOCs. Criticisms of MOOCs Khan Academy The organization is unclear and it lacks sufficient learner support.The videos aren’t informed by research and theory on how people learn, and this may diminish the effectiveness of his videos. Are MOOCs a Horseless Carriage? In the book How People Learn (which can be read free online), John Bransford shared the story of Fish is Fish. MOOC or MMORPG? From MOOC to MOOLE Who’s the teacher in a MOOLE?
Experts on the Pros and Cons of Algorithms Algorithms are instructions for solving a problem or completing a task. Recipes are algorithms, as are math equations. Computer code is algorithmic. The internet runs on algorithms and all online searching is accomplished through them. Email knows where to go thanks to algorithms. Algorithms are often elegant and incredibly useful tools used to accomplish tasks. The British pound dropped 6.1% in value in seconds on Oct. 7, 2016, partly because of currency trades triggered by algorithms.Microsoft engineers created a Twitter bot named “Tay” this past spring in an attempt to chat with Millennials by responding to their prompts, but within hours it was spouting racist, sexist, Holocaust-denying tweets based on algorithms that had it “learning” how to respond to others based on what was tweeted at it.Facebook tried to create a feature to highlight Trending Topics from around the site in people’s feeds. Theme 1: Algorithms will continue to spread everywhere Theme 2: Good things lie ahead