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Can someone explain what are some machine learning algorithms that you should always have a strong understanding of, and why?

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Some of the algorithms of Machine Learning that form the base of the technology and that you should have a strong knowledge of are as follows:

  • Linear regression: It is used when there is a need to build a relationship between the input and the output variables. It aims to find the required line fitting all the data and can be represented by the equation, y = ax + b

  • Logical regression: It allows you to find if a particular event is possible to occur in the future. It offers the binary form of data and the result can either be 0 or 1. 

  • Principal component analysis: It allows professionals to visualize the data and enable the mode that allows one to add variables. Moreover, it has the feature elimination option that allows one to remove all the extra and unnecessary features.

  • Naive Bayes: It is the most preferable algorithm as it is easy and simple for the development approach. It significantly comes in handy while calculating the hypothesis probability.

  • K-means clustering: This algorithm plays an important role when there is no supervision in the existing algorithms and that leads to an issue in clustering.

To master these algorithms and become an expert in this field, you must apply for Machine Learning Training at Intellipaat and learn from professionals who have over 12 years of working experience in it.

Check out this YouTube video tutorial to gain a better insight into Machine Learning:

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