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    Write a note on devising validating and testing of algorithm

    Integration is an important concept in mathematics and, together with its inverse, differentiation, is one of the two main operations in calculus.

    Given a function f of a real variable x and an interval [a, b] of the real line, the definite integral is defined informally to be the area of the region in the xy-plane bounded by the graph of f, the x-axis, and the vertical lines x = a and x = b, such that areas above the axis add to the total, and the area below the x axis subtract from the total.

    In mathematics, an elementary function is a function of one variable built from a finite number of exponentials, logarithms, constants, and nth roots through composition and combinations using the four elementary operations ( ¿ × ÷).

    By allowing these functions (and constants) to be complex numbers, trigonometric functions and their inverses become included in the elementary functions.

    You will discover what feature engineering is, what problem it solves, why it matters, how to engineer features, who is doing it well and where you can go to learn more and get good at it.

    If you read one article on feature engineering, I want it to be this one.

    The logarithm of a number is the exponent by which another fixed value, the base, has to be raised to produce that number.

    write a note on devising validating and testing of algorithm-30write a note on devising validating and testing of algorithm-25

    This includes getting the best results from the algorithms you are using.Software testing can also provide an objective, independent view of the software to allow the business to appreciate and understand the risks of software implementation.Test techniques include, but are not limited to, the process of executing a program or application with the intent of finding software bugs (errors or other defects).feature engineering is another topic which doesn’t seem to merit any review papers or books, or even chapters in books, but it is absolutely vital to ML success.[…] Much of the success of machine learning is actually success in engineering features that a learner can understand.

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