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    Aryabhatta

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    | A Brief History of MathematicsPeople seem compelled to organize. They also have a practical need to count certain things: cattle‚ cornstalks‚ and so on. There is the need to deal with simple geometrical situations in providing shelter and dealing with land. Once some form of writing is added into the mix‚ mathematics cannot be far behind. It might even be said that the symbolic approach precedes and leads to the invention of writing.Archaeologists‚ anthropologists‚ linguists and others studying

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    This hypothesis was supported in the data recorded and final graph shown above. The final graph has a polynomial trendline‚ which has a resemblance trend as the graph in the hypothesis section. Moreover‚ it has shown that the highest temperature (39 OC) had the greatest rate of cellular respiration and comparatively lower rate at 19 OC. By theory‚ temperature

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    Vectors in Two Dimensions‚ Mathematics in Practical situation‚ Graphs in Practical Situations 4. Ten Years Series Additional Mathematics 1. Secondary Three Topics- Simultaneous Eqn‚ Surds Indices & Log‚ Quadratic Eqn & inequalities‚ Polynomials & Partial Fractions‚ The Modulus Function‚ Biomial Theorem‚ Coordinate Geometry‚ Linear Law‚ Trigo Functions 2. Secondary Four Topics- Simple Trigo Identities & Eqn‚ Further Trigo Identities‚ Differentiation‚ Rates of Change‚ Maxima & Minima

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    Machine Learning

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    Definition Tom M. Mitchell provided a widely quoted definition: A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P‚ if its performance at tasks in T‚ as measured by P‚ improves with experience E.[1] Generalization Generalization is the ability of a machine learning algorithm to perform accurately on new‚ unseen examples after training on a finite data set. The core objective of a learner is to generalize from its experience

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    Geometry formula list

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    Graded Assignment Unit Test‚ Part 2: Polynomials and Power Functions Answer the questions and show your work. When you are finished‚ submit this assignment to your teacher through the appropriate dropbox basket. (3 pts) 1.) Factor 100x^2 – 49 to factor‚ use the difference of squares formula‚ because both the terms are perfect squares the difference of squares formula is a^2 – b^2 = (a-b)(a+b) therefore 100x^2 – 49 = (10x)^2 – 7^2 = (10x – 7)(10x +7) (5 pts) 2.) Solve x^2 –

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    Linear Progamming

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    Linear Programming Tools and Approximation Algorithms for Combinatorial Optimization by David Alexander Griffith Pritchard A thesis presented to the University of Waterloo in fulfillment of the thesis requirement for the degree of Doctor of Philosophy in Combinatorics and Optimization Waterloo‚ Ontario‚ Canada‚ 2009 c David Alexander Griffith Pritchard 2009 I hereby declare that I am the sole author of this thesis. This is a true copy of the thesis‚ including any required final revisions

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    C1 C2 M1 Revision

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    Core 1 Linear Graphs and Equations For any straight line‚ the gradient (M) is: dy/dx or difference in y/difference in x which is (y2-y1)/(x2-x1) Equation of a line: y=mx+c which is used when the gradient and intercept is known or y-y1=m(x-x1) when the gradient and the co-ordinates (x1‚y1) of a single point that the line passes through is known. You’ll need to learn this equation. [The equation of the line can be kept in this form unless stated in the exam. (reduces error chance) Also

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    The Golden Ratio

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    The Golden Ratio By : Kaavya.K In mathematics and the arts‚ two quantities are in the golden ratio if the ratio of the sum of the quantities to the larger quantity is equal to the ratio of the larger quantity to the smaller one. The golden ratio is an irrational mathematical constant‚ approximately 1.6180339887. Other names frequently used for the golden ratio are the golden section and golden mean. Other terms encountered include extreme and mean ratio‚ medial section‚ divine

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    ISLR Fourth Printing

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    Springer Texts in Statistics Series Editors: G. Casella S. Fienberg I. Olkin For further volumes: http://www.springer.com/series/417 Gareth James • Daniela Witten • Trevor Hastie Robert Tibshirani An Introduction to Statistical Learning with Applications in R 123 Gareth James Department of Information and Operations Management University of Southern California Los Angeles‚ CA‚ USA Daniela Witten Department of Biostatistics University of Washington Seattle‚ WA‚ USA Trevor Hastie Department

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    Math Class

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    |equations and inequalities‚ graphing linear equations in two variables‚ solving systems of linear | | |equations in two variables‚ operations with exponential expressions and polynomials‚ factoring | |

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