Tensors and vectors  Python for Integrated Circuits   An Online Book  

Python for Integrated Circuits http://www.globalsino.com/ICs/  


Chapter/Index: Introduction  A  B  C  D  E  F  G  H  I  J  K  L  M  N  O  P  Q  R  S  T  U  V  W  X  Y  Z  Appendix  
================================================================================= In TensorFlow library, tensors are the building blocks as all computations are done using tensors. Googleâ€™s TensorFlow team says, "A tensor is a generalization of vectors and matrices to potentially higher dimensions. Internally, TensorFlow represents tensors as ndimensional arrays of base datatypes." Tensors can be of two types: A vector is understood as something that has a magnitude and a direction. Without the direction of a vector, a tensor becomes a scalar value that has only magnitude. A vector is used to represent n number of things and can represent area and different attributes, among other things. If a vector is multiplyed with another vector, a scalar quantity is obtained, while if a vector is multiplyed with a scalar value, it just increases or decreases in the same proportion, in terms of its magnitude, without changing its direction. However, if a vector is multiplyed with a tensor, it then will result in a new vector that has a changed magnitude as well as a new direction. In pandas, a series object represents a vector of data. Script to output a vector: ============================================


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