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Quick tour (FAQ)

1. What is an algorithm?
An algorithm is a procedure or formula for solving a problem, based on conducting a sequence of specified actions. Let’s say when you’re preparing an omelette… then your ingredients (eggs, tomatoes, cheese) are the data and the recipe (fry the egg, slice the tomato, add the cheese) is the algorithm.

According to Techtarget a computer program can be viewed as an elaborate algorithm. In mathematics and computer science, an algorithm usually means a small procedure that solves a recurrent problem.
 
2. Where does the name “Algorithm” come from?
The word algorithm derives from the name of the mathematician, Mohammed ibn-Musa al-Khwarizmi, who was part of the royal court in Baghdad and who lived from about 780 to 850. Al-Khwarizmi’s work is the likely source for the word algebra as well. So, the Latinized version of this Arabic name is why we call it AL-go-rithm. It has nothing to do with former Vice President Al Gore.
 
3. Hm, I think I need an algorithm crash-course!
Khan Academy provides an introductory tutorial on algorithms:

 

4. So why do we need another Hall of Fame?
Because algorithms don’t get enough credit! People love to talk about data all the time, but they forget that without algorithms their data is just ones and zeros. It’s actually algorithms that make the world go round.

Inspired by the Internet Hall of Fame we decided that there should be an honorary list of algorithms too. So we asked the public (scientists, business people and you) which algorithms should get more attention. And our expert jury will decide which of those will be officially inducted into the Algorithm Hall of Fame.
 

5. I am ready for some example of algorithms!
 

Examples in Machine Learning

  • Linear Regression
  • Logistic Regression
  • Decision Tree
  • Support Vector Machine (SVM)
  • Naive Bayes
  • K-Nearest Neighbors (KNN)
  • K-Means
  • Random Forest
  • Gradient Descent

Examples in cryptography

  • DES
  • RSA
  • HASH
  • MD5
  • AES
  • SHA-1
  • HMAC
 

Algorithms in data mining

  • C4.5
  • K-means
  • Support vector machines
  • Apriori
  • EM
  • PageRank
  • AdaBoost
  • kNN

Other applications

  • Process digital images
  • Find the shortest path between two points
  • Crypto-mining
  • Amortization
  • Randomization
  • Fingerprinting
  • Bit scaling
  • Dynamic programming
  • Network flow
  • Linear programming
 

6. How can I help?

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