Machine Learning is undoubtedly the most in-demand technology of the era! If you’re a beginner who’s getting started with Machine Learning, it’s important you know the prerequisites for Machine Learning. This blog will help you understand the different concepts that you need to know before you get started with Machine Learning.
Pre-requisites For Machine Learning:
To get started with Machine Learning you must be familiar with the following concepts:
Statistics
Linear Algebra
Calculus
Probability
Programming Languages
Statistics:
Statistics contain tools that can be used to get some outcome from the data. There is descriptive statistics which is used to transform raw data in some important information. Also, inferential statistics can be used to get important information from a sample of data instead of using complete dataset.
Linear Algebra:
Linear algebra deals with vectors, matrices, and linear transformations. It is very important in machine learning as it can be used to transform and perform operations on the dataset.
Calculus:
Calculus is an important field in mathematics and it plays an integral role in many machine learning algorithms. Data set having multiple features are used to build machine learning models as features are multiple multivariable calculus plays an important role to build a machine learning model. Integrations and Differentiations are a must.
Probability:
Probability helps to predict the likelihood of the occurrences, It helps us to reason the situation may or may not happen again. For machine learning, probability is a foundation.
Programming language:
It is essential to know programming languages like R and Python in order to implement the whole Machine Learning process. Python and R both provide in-built libraries that make it very easy to implement Machine Learning algorithms.
Apart from having basic programming knowledge, it is also important that you know how to extract, process and analyze data. This is one of the most important skills that is needed for Machine Learning.
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