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Learn Data Structures and Algorithms with Golang

You're reading from   Learn Data Structures and Algorithms with Golang Level up your Go programming skills to develop faster and more efficient code

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Product type Paperback
Published in Mar 2019
Publisher Packt
ISBN-13 9781789618501
Length 336 pages
Edition 1st Edition
Languages
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Author (1):
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Bhagvan Kommadi Bhagvan Kommadi
Author Profile Icon Bhagvan Kommadi
Bhagvan Kommadi
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Table of Contents (16) Chapters Close

Preface 1. Section 1: Introduction to Data Structures and Algorithms and the Go Language FREE CHAPTER
2. Data Structures and Algorithms 3. Getting Started with Go for Data Structures and Algorithms 4. Section 2: Basic Data Structures and Algorithms using Go
5. Linear Data Structures 6. Non-Linear Data Structures 7. Homogeneous Data Structures 8. Heterogeneous Data Structures 9. Dynamic Data Structures 10. Classic Algorithms 11. Section 3: Advanced Data Structures and Algorithms using Go
12. Network and Sparse Matrix Representation 13. Memory Management 14. Next Steps 15. Other Books You May Enjoy

Homogeneous Data Structures

Homogeneous data structures contain similar types of data, such as integers or double values. Homogeneous data structures are used in matrices, as well as tensor and vector mathematics. Tensors are mathematical structures for scalars and vectors. A first-rank tensor is a vector. A vector consists of a row or a column. A tensor with zero rank is a scalar. A matrix is a two-dimensional cluster of numbers. They are all used in scientific analysis.

Tensors are used in material science. They are used in mathematics, physics, mechanics, electrodynamics, and general relativity. Machine learning solutions utilize a tensor data structure. A tensor has properties such as position, shape, and a static size.

This chapter covers the following homogeneous data structures:

  • Two-dimensional arrays
  • Multi-dimensional arrays

The following scenarios are shown to demonstrate...

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