Algorithms

 What is an Algorithm?



"In Mathematics and computer science, an algorithm is a finite sequence of well-defined, computer-implementable instructions, typically to solve a class of problems or to solve a class of problems or to perform a computation."

In simple words, an algorithm is a step-by-step procedure to solve any problem.

Why Data Scientists need to learn Algorithms? 

  • Knowledge of data structures & algorithms is useful for data scientists because our solutions are inevitably written in code. As such, it is important to understand the structure of data and how to think in terms of algorithms.
  • As the role of a Data Scientist is to solve complex problems by performing custom data analysis by designing the model so there is a need to learn algorithms. 

Types of Algorithms in Machine Learning

  1. Linear Regression 
  2. Logistics Regression
  3. KNN 
  4. K-Means Clustering
  5. Naive Bayes 
  6. Decision Tree 
  7. Random Forest
These Machine Learning algorithms can be used to solve business problems like Regression, Classification, Forecasting, Clustering, and Associations, etc.






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