#107 Machine Learning & Data Science Challenge 107
Greetings.
I am a machine learning engineer based in India, possessing a sustained interest in machine learning since my undergraduate studies. I have completed Stanford University's machine learning course (Andrew Ng) via Coursera, and IBM's machine learning and deep learning curriculum. My current focus is on machine learning and data science projects, aiming to leverage my expertise for impactful, real-world problem-solving.
What are Tensors?
In mathematics, it is an algebraic object that describes the linear mapping from one set of algebraic objects to another.
Objects that the tensors may map between include, but are not limited to the vectors, scalars, and recursively, even other tensors (for example, a matrix is a map between vectors and thus a tensor. Therefore the linear map between matrices is also the tensor).
Tensors are inherently related to vector spaces and their dual spaces and can take several different forms.
For example, a scalar, a vector, a dual vector at a point, or a multi-linear map between vector spaces.
Euclidean vectors and scalars are simple tensors. While tensors are defined as independent of any basis.
The physics literature is often referred to by its components on a basis related to a particular coordinate system.
