Think of all the psychic energy expended in seeking a fundamental distinction between “algorithm” and “program”.
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### Mohamed Ennahdi El Idrissi

Resources  -

A useful tool for algorithm analysis fans:

www.combineditorix.com﻿
Summation/Product, Number of Nested Loops, From, To, Term. 1. Summation Product. Var, Value. Var, Value. OK. When $a \ne 0$, there are two solutions to $$ax^2 + bx + c = 0$$ and they are $$x = {-b \pm \sqrt{b^2-4ac} \over 2a}.$$
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### Mohamed Ennahdi El Idrissi

Algorithms  -
Reading the so called paper "Discrete Loops and Worst Case Performance" (by Dr. Johann Blieberger), I came across some interesting summations: Useful here: for ( i = 1; i <= n ; i ++ ) { for (j = 1; j <= i ; j ...
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### unmesha sreeveni

Algorithms  -

How To Workout SVM Algorithm In machine learning, support vector machines (SVMs, also support vector networks) are supervised learning models with associated learning alg...
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### Mohamed Ennahdi El Idrissi

Algorithms  -

A continuation of the introduction about algorithms - Algorithm Analysis.

http://mohalgorithmsorbit.blogspot.com/2013/12/algorithms-debut-iii-algorithm-analysis.html﻿
Grasping algorithmic notions utilizing a programming language, along with data structures are enough to engage into writing computer programs and applications. With a little of experience, a thoughtful programmer would expre...
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Algorithms  -
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### Xan Phillips

Discussions  -

Having just joined I noticed the quote at the top and thought of an answer. I hope this isn't repeating a previous conversation, but could the distinction between “algorithm” and “program” be this...

An algorithm gives you an answer where as a program helps you do things.﻿
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Algorithms  -
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### unmesha sreeveni

Algorithms  -

How To Workout Decision Tree Algorithm Decision Tree Induction is the learning of decision trees from class-labeled training tuples. A decision tree is a flowchart-like tree structure, where each internal node (nonleaf no...
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### unmesha sreeveni

Algorithms  -

A Naive Bayes Classifier is a simple probabilistic classifier based on applying Bayes' theorem with strong (naive) independence assumptions.The main advantage of naive Bayes is that it only requires a smaller amount of data f...
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