Maxima, a Computer Algebra System numexpr - Fast numerical array expression evaluator for Python and NumPy. Please be aware that the numexpr project has been migrated to GitHub. This site has been declared unmaintained as of 2014-01-21. Sorry for the inconveniences. -- Francesc Alted What It Is The numexpr package evaluates multiple-operator array expressions many times faster than NumPy can. Also,numexpr implements support for multi-threading computations straight into its internal virtual machine, written in C. It is also interesting to note that, as of version 2.0, numexpr uses the new iterator introduced in NumPy 1.6 so as to achieve better performance in a broader range of data arrangements. Finally, numexpr has support for the Intel VML (Vector Math Library) -- integrated in Intel MKL (Math Kernel Library) --, allowing nice speed-ups when computing transcendental functions (like trigonometrical, exponentials...) on top of Intel-compatible platforms. Examples of Use Using it is simple: >>> import numpy as np>>> import numexpr as ne >>> a = np.arange(1e6)>>> b = np.arange(1e6) and fast...
Online texts Professor Jim Herod and I have written Multivariable Calculus ,a book which we and a few others have used here at Georgia Tech for two years. We have also proposed that this be the first calculus course in the curriculum here, but that is another story.... Although it is still in print, Calculus,by Gilbert Strang is made available through MIT's OpenCourseWare electronic publishing initiative. Here is one that has also been used here at Georgia Tech. Linear Methods of Applied Mathematics, by Evans Harrell and James Herod. Recommendation System in R Recommender systems are used to predict the best products to offer to customers. These babies have become extremely popular in virtually every single industry, helping customers find products they'll like. Most people are familiar with the idea, but nearly everyone is exposed to several forms of personalized offers and recommendations each day (Google search ads being among the biggest source). Building recommendation systems is part science, part art, and many have become extremely sophisticated. Such a system might seem daunting for those uninitiated, but it's actually fairly straight forward to get started if you're using the right tools. This is a post about building recommender systems in R. UPDATE: We used the beer / product recommender for a talk at PyData Boston in July. Beer Dataset "Respect Beer." - BeerAdvocate.com For this example, we'll use data from Beer Advocate, a community of beer enthusiasts and industry professionals dedicated to supporting and promoting beer.
Welcome to OpenModelica Sage - French Math Alive Course Instructors Ingrid DaubechiesShannon Hughes 218 (ID)/217 (SH) Fine Hall, Washington Road Princeton, NJ 08540-1000 You can find other contact information on a Contact us page. How is life different from 25 or even 10 years ago? Cryptography Error correction & compression Probability & Statistics Birth, Growth, Death & Chaos Graph Theory Voting & Social Choice You can navigate through the units using the navigation bar on the left. Each unit is divided into two parts. Don't forget to check the latest announcements on the Announcements page. Problem Sets: You need to look at the On-Line Labs and at the Problem Sets (clickable on the left). The videotaped lectures of Spring 2003 course are available on blackboard. References: For All Practical Purposes : Introduction to Contemporary Mathematics. 4th edition (December 1997). If you have any questions, Send Mail To: Math Alive Help
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