We will start with Linear Algebra basics. I might be posting 2 or 3 more articles on Linear Algebra to cover those topics which are relevant to machine learning. The topics to be discussed are listed as follows:-
In this particular article, we will start with Linear Algebra basics. I might be posting 2 or 3 more articles on Linear Algebra to cover those topics which are relevant to machine learning. The topics to be discussed are listed as follows:-
*Vectors:- *It is an object that has both magnitudes as well as the direction. Geometrically, we can visualize a vector as a directed line segment whose length gives the magnitude of the vector and arrow gives the direction.
In machine learning, we use vectors to represent features and labels of the input data like age, salary, etc. Here in this example, V is a two- dimensional vector from the field of Real Numbers.
*Vector Space:- *A vector space is a set V of vectors on which the vector addition and vector multiplication are defined such that,
The hidden engine of machine learning. Algebra is firstly taken from a book, written by Khwarizmi(780-850 CE), which is about calculation and equations.
Basic Mathematical Concepts for Machine Learning. Machine learning at its base is complete and pure mathematics and logic.
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AI, Machine learning, as its title defines, is involved as a process to make the machine operate a task automatically to know more join CETPA
These notes are intended to provide a “fast” collection of theoretical definitions, theorems, and concepts for Linear Algebra as a refresher only