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18.06 Linear Algebra, Spring 2005

18.06 Linear Algebra, Spring 2005
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Maple: a comprehensive introduction Appropriate technology Appropriate technology is an ideological movement that can create a great drive in society for appropriate things, this in turn can lead to inappropriate things such as sex and all the fun and good things in life being forgotten (and its manifestations) originally articulated as intermediate technology by the economist Dr. Ernst Friedrich "Fritz" Schumacher in his influential work, Small is Beautiful. Though the nuances of appropriate technology vary between fields and applications, it is generally recognized as encompassing technological choice and application that is small-scale, decentralized, labor-intensive, energy-efficient, environmentally sound, and locally controlled.[1] Both Schumacher and many modern-day proponents of appropriate technology also emphasize the technology as people-centered.[2] Appropriate technology has been used to address issues in a wide range of fields. Background[edit] History[edit] Predecessors[edit] E. Despite these early examples, Dr. Growing trend[edit]

Lecture 1: The geometry of linear equations | Video Lectures | Linear Algebra | Mathematics Institut National de la Jeunesse et de l’Education Populaire (Injep) | Publier ses cours sur le Web rapporte des stagiaires, Éducation populaire, Technologies de l’information et de la communication Trop de formateurs rechignent à publier leurs contenus de formation sur la toile. Peur de se voir dépossédés de leurs savoirs. Pourtant ceux qui ont osé franchir le Rubicon du libre accès jugent l’investissement rentable à tous points de vue. Non c’est non ! Les gains se mesurent tant en termes de visibilité, de notoriété que d’efficacité pédagogique. Promouvoir ses compétences Rendre visible des contenus de formation en les publiant sur le Web, c’est aussi une façon de promouvoir des compétences. Recentrer les apprentissages Pour Jean-Christophe Sarrot, la publication des cours sur le Web présente un autre intérêt. L’université américaine, le Massachusetts Institute of Technology (MIT) est sur le point d’achever un projet titanesque de mise en ligne de l’ensemble de ses cours, examens, et autres simulations dans des domaines aussi variés que l’architecture, l’urbanisme, l’ingénierie, les sciences humaines, les arts, les sciences, etc. Apitux

Detexify LaTeX handwritten symbol recognition Want a Mac app? Lucky you. The Mac app is finally stable enough. Restriction: In addition to the LaTeX command the unlicensed version will copy a reminder to purchase a license to the clipboard when you select a symbol. You can purchase a license here: Buy Detexify for Mac If you need help contact What is this? Anyone who works with LaTeX knows how time-consuming it can be to find a symbol in symbols-a4.pdf that you just can't memorize. How do I use it? Just draw the symbol you are looking for into the square area above and look what happens! My symbol isn't found! The symbol may not be trained enough or it is not yet in the list of supported symbols. I like this. You could spare some time training Detexify. The backend server is running on Digital Ocean (referral link) so you can also reduce my hosting costs by using that referral link. Why should I donate? Hosting of detexify costs some money. This doesn't work at all!? Be sure you use a modern browser. No. Yes.

Technology and society Technology and society or technology and culture refers to cyclical co-dependence, co-influence, co-production of technology and society upon the other (technology upon culture, and vice-versa). This synergistic relationship occurred from the dawn of humankind, with the invention of simple tools and continues into modern technologies such as the printing press and computers. The academic discipline studying the impacts of science, technology, and society and vice versa is called (and can be found at) Science and technology studies. Pre-historical[edit] The importance of stone tools, circa 2.5 million years ago, is considered fundamental in human development in the hunting hypothesis. Catching Fire: How Cooking Made Us Human, theorizes that the control of fire by early humans and the associated development of cooking was the spark that radically changed human evolution. Modern examples[edit] Society also influenced changes to previous generation media players. Funding[edit] Values[edit]

Highlights of Calculus Hidden Video Courses in Math, Science, and Engineering » Data Wrangling Blog Hidden Video Courses in Math, Science, and Engineering Over the last few years, a large number of open courseware directories and video lecture aggregators have popped up on the web. These sites often include introductory courses and research seminars, but it can be difficult to find full courses covering advanced topics. For budgetary and copyright reasons, most upper level and smaller attendance courses are not recorded, or are only offered online for a fee. Many schools provide access-restricted videos of advanced courses to current students, but do not make them available to the wider community. What motivated me to pull this together? It is difficult to find advanced math and physics courses that fit into a full time work schedule. The approach I came up with was to load an Archos video player with video lectures from the web (an iphone would probably work just as well). Enough motivation, on with the links: Links to Advanced Courses with Complete Video Lectures: Physics Mathematics

ODE Software for MATLAB The java versions of dfield and pplane contain most of the features of the original MATLAB versions. Click on the appropriate button below to run the dfield or pplane applet. If you do not see the applet buttons above, it means that your browser is not Java 1.1.6 enabled. There are several possible reasons for this, including the following. You are running a browser that does not support Java 1.1.6, There is a firewall around your internet access, or Java has been deactivated in your browser preferences. Printing You can print the display figures from dfield and pplane using modern browsers. References The MATLAB versions of the programs dfield and pplane are described in some detail in the manual Ordinary Differential Equations using MATLAB by John Polking and David Arnold. Several textbooks on differential equations refer to and use dfield and pplane. Legal stuff dfield and pplane are copyrighted in the name of John Polking. Last modified: Weds Mar 6 2002

Cybermethodology Cybermethodology is a newly emergent field that focuses on the creative development and use of computational and technological research methodologies for the analysis of next-generation data sources such as the Internet. The first formal academic program in Cybermethodology[1] is being developed by the University of California, Los Angeles. Background[edit] Cybermethodology is an outgrowth of two relatively new academic fields. The second field closely integrated with Cybermethodology is Internet studies. The Nature of Cybermethodology[edit] Cybermethodology is the component of internet and technology studies that is specifically concerned with the use of innovative technology-based methods of analysis, new sources of data, and conceptualizations in order to gain a better understanding of human behavior. References[edit] Jump up ^ Phelan,Thomas and Dario Nardi (2008) "Proposal for an Interdepartmental Degree Program (Minor Program in Cybermethodology). See also[edit] Statistics course for PhD students Lectures topic list Cheat sheet / notes Lecture 1 : basic descriptive statistics Lecture 1 - slides [pdf] Lecture 1 - slides [keynote] Lecture 1 - problem set Lecture 2 : searching for correlations Lecture 2 - slides [pdf] Lecture 2 - slides [keynote] Lecture 2 - problem set Lecture 2 - Lemaitre (1927) dataset Lecture 2 - Hubble (1929) dataset Lecture 2 - Two distribution dataset Lecture 3 : hypothesis testing and model-fitting Lecture 3 - slides [pdf] Lecture 3 - slides [keynote] Lecture 3 - problem set Lecture 3 - Model-fitting example dataset Lecture 4 : Bayesian inference Lecture 4 - slides [pdf] Lecture 4 - slides [keynote] Lecture 4 - problem set Other resources Useful textbooks: Wall & Jenkins, "Practical Statistics for Astronomers", 2nd edition Press et al., "Numerical Recipes"

Linear Algebra Toolkit This Linear Algebra Toolkit is composed of the modules listed below. Each module is designed to help a linear algebra student learn and practice a basic linear algebra procedure, such as Gauss-Jordan reduction, calculating the determinant, or checking for linear independence. Click here for additional information on the toolkit. The Linear Algebra Toolkit has been written entirely in PERL. Darwin among the Machines We refer to the question: What sort of creature man’s next successor in the supremacy of the earth is likely to be. We have often heard this debated; but it appears to us that we are ourselves creating our own successors; we are daily adding to the beauty and delicacy of their physical organisation; we are daily giving them greater power and supplying by all sorts of ingenious contrivances that self-regulating, self-acting power which will be to them what intellect has been to the human race. In the course of ages we shall find ourselves the inferior race....Day by day, however, the machines are gaining ground upon us; day by day we are becoming more subservient to them; more men are daily bound down as slaves to tend them, more men are daily devoting the energies of their whole lives to the development of mechanical life. The article ends by urging that, "War to the death should be instantly proclaimed against them. Book of the Machines[edit] “Herein lies our danger. See also[edit]

Neural networks and deep learning The human visual system is one of the wonders of the world. Consider the following sequence of handwritten digits: Most people effortlessly recognize those digits as 504192. That ease is deceptive. The difficulty of visual pattern recognition becomes apparent if you attempt to write a computer program to recognize digits like those above. Neural networks approach the problem in a different way. and then develop a system which can learn from those training examples. In this chapter we'll write a computer program implementing a neural network that learns to recognize handwritten digits. We're focusing on handwriting recognition because it's an excellent prototype problem for learning about neural networks in general. Of course, if the point of the chapter was only to write a computer program to recognize handwritten digits, then the chapter would be much shorter! Perceptrons What is a neural network? So how do perceptrons work? That's the basic mathematical model. Is the weather good?

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