Guest Post: Information Retrieval using a Bayesian Model of Learning and Generalization Dinesh Vadhia, CEO and founder of “item search” company Xyggy, has been an active member of the Noisy Community for at least a year, and it is with pleasure that I publish this guest post by him, University of Cambridge / CMU Professor Zoubin Ghahramani, and University of Cambridge / Gatsby Computational Neuroscience Unit researcher Katherine Heller. I’ve annotated the post with Wikipedia links in the hope of making it more accessible to readers without a background in statistics or machine learning. People are very good at learning new concepts after observing just a few examples. Bayesian Sets is a new framework for information retrieval based on how humans learn new concepts and generalize. Bayesian Sets – a novel framework for information retrieval An individual item is represented by a vector of features of that item. A concept can be characterized by using a statistical model, which defines the generative process for the features of items belonging to the concept. The score Uses
Twisted Documentation: Twisted Documentation Go to the latest version of this document. Introduction Executive summary Connecting your software - and having fun too! Getting Started Networking and Other Event Sources Twisted Internet A brief overview of the twisted.internet package. Reactor basics The event loop at the core of your program. Using SSL in Twisted Add some security to your network transport. UDP Networking Multicast too! Index Version: 13.2.0 python.ayukucode alexksikes/mass-scraping - GitHub PyFlickrStreamr 0.1 Package Index > PyFlickrStreamr > 0.1 Not Logged In Status Nothing to report PyFlickrStreamr 0.1 Download PyFlickrStreamr-0.1.tar.gz PyFlickrStreamr provides a continuous, blocking python interface for streaming Flickr photos in near real-time. ============= PyFlickrStreamr ============= PyFlickrStreamr provides a continuous, blocking python interface for streaming Flickr photos in near real-time. Downloads (All Versions): 5 downloads in the last day 38 downloads in the last week 179 downloads in the last month Website maintained by the Python community Real-time CDN by Fastly / hosting by Rackspace / design by Tim Parkin
Home | Read the Docs Faceted Search With Sphinx I decided to use the Sphinx search engine for the GeeQe iPhone app I build last year because it was fast and had a very small memory footprint. Recently I wanted to experiment with a search interface that had facets and wondered if I would need to move away from Sphinx to something like Solr. As it turns out Sphinx can do faceted search almost as well as Solr can. You have almost certainly seen faceted searching or faceted browsing already. In each of the above cases you will find the left hand navigation displaying the facets. One of the ways facets are useful is the ability to drill down into the results and create filters based on the facets. Some sites build a breadcrumb of facets you have selected as you drill down into the results. Now that you have some examples of what faceted search looks like we can move on to creating the same using Sphinx. If you haven't already, now is the time to install Sphinx. You should now be able to test against the index.
The Eric Python IDE Python Faceted search Facets correspond to properties of the information elements. They are often derived by analysis of the text of an item using entity extraction techniques or from pre-existing fields in a database such as author, descriptor, language, and format. Thus, existing web-pages, product descriptions or online collections of articles can be augmented with navigational facets. Development[edit] The Association for Computing Machinery's Special Interest Group on Information Retrieval provided the following description of the role of faceted search for a 2006 workshop: The web search world, since its very beginning, has offered two paradigms:Navigational search uses a hierarchy structure (taxonomy) to enable users to browse the information space by iteratively narrowing the scope of their quest in a predetermined order, as exemplified by Yahoo! Projects[edit] The most notable academic efforts in faceted search are the following: Mass market use[edit] Online retail[edit] Libraries[edit] See also[edit]
Recetario - PyAr - Python Argentina Nuestro CookBook, en vías desarrollo. A este lugar uno recurre cada vez que se encuentra en la cocina de Python, cuchillo en mano y se da cuenta que a sus ingredientes le faltan el toque de un cheff experto. Nuestra especialidad son las recetas autóctonas. ¿Platos magistrales que fallan al sazonar con acentos y eñes? ¿números que saben mal si no son previamente fritos en castellano? ¡Siga leyendo! 1. 1.1. Recetario/CreandoUnNuevoProyectoPython: Receta para crear un entorno de trabajo y un esqueleto minimo para un nuevo proyecto Python 1.2. Autocompletado en consola interactiva: tip sobre como agregar autocompleción con tab en la consola interactiva imitando el comportamiento ipython. 2. 2.1. 3. 3.1. /ExtraerMails de un texto utilizando el módulo re. 4. 4.1. aLetras aLetras : Función que al recibir un número lo convierte a letras. 4.2. Reverse : Función que invierte los caracteres. 4.3. validar_cuit /ValidarCuit : Función para validar un CUIT/CUIL estilo 00-00000000-0 4.5. 4.6. 5. 5.1. 5.2. 6.
首頁 - Python_NoteBook From Python_NoteBook 2010.04.01磺嘴山上面的大樹蛙........蛙挖哇.蛙蛙蛙蛙...用力的蛙 有趣的東西太多，能用的時間太少，真正專心的時間更少 ==最新文章== 2008.03.04很久沒有更新首頁的圖了........挖阿.挖阿...用力的挖 看看是否可以找到前輩的偷偷藏起來的骨頭 圖片欣賞 本網站不是在賣花的 ~~笑 建立網站的目的就是為了要將自己平常的工作 或是遇到的問題加以整理，以後要再用得時候就很快了 如果大家可以在上面找到有用的情報的話歡迎多多利用與指教 取之於網路用之於網路 免責聲明 本網站對於任何使用或引用本網站網頁資料引致之損失或損害，概不負責。 © Copyright 2010 mechanize Stateful programmatic web browsing in Python, after Andy Lester’s Perl module WWW::Mechanize. The examples below are written for a website that does not exist (example.com), so cannot be run. There are also some working examples that you can run. import reimport mechanize br = mechanize.Browser()br.open(" follow second link with element text matching regular expressionresponse1 = br.follow_link(text_regex=r"cheese\s*shop", nr=1)assert br.viewing_html()print br.title()print response1.geturl()print response1.info() # headersprint response1.read() # body br.select_form(name="order")# Browser passes through unknown attributes (including methods)# to the selected HTMLForm.br["cheeses"] = ["mozzarella", "caerphilly"] # (the method here is __setitem__)# Submit current form. # print currently selected form (don't call .submit() on this, use br.submit())print br.form mechanize exports the complete interface of urllib2:
s Python Class - Google's Python Class - Google Code Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. To get started, the Python sections are linked at the left -- Python Set Up to get Python installed on your machine, Python Introduction for an introduction to the language, and then Python Strings starts the coding material, leading to the first exercise.