This course is an introduction to Tensor calculations with Eigen, a popular C++ library for working with numerical arrays and linear algebra. It covers the following topics:
- We learn the concept and techniques of the Eigen Tensor class
- How to declare, initialize Tensors of various ranks and types and how to access Tensor elements
- Elementary unary and binary operations involving Tensors
- More complex operations (reductions, contractions)
- Modifying the shape of Tensors
Who Is This Course For:
Developers in any Domain that need to use higher-dimensional numerical data containers
- Statistical Calculations
- Machine Learning
How Does The Course Help:
Eigen is a fairly large library. The course aims to:
- Introduce the Tensor part of the library and its purpose
- Sketch its overall structure and functionality
- Familiarize with the common usage patterns (API's)
What Will You Get From The Course:
- You will be able to confidently use Eigen::Tensor to solve common numerical processing tasks, in particular those requiring standard manipulation of tensors
- You will be able to contribute to the specific use cases mentioned above
Course Level and Difficulty Level:
This course is part of the Data Science family.
- This is a Core Level course in Data Science, which means that good grounding at Introductory level to various Data Science topics is a prerequisite for making the most out of this course.
- This is a Technical course which means certain mathematical (linear algebra) and/or technology elements (C++) are assumed as known before one can master the course material.
Advanced material not covered here:
- Memory layouts (how numerical data are stored in memory) and the performance implications
- Extending Eigen (in particular the C-API's)
- Numerical algebra / scientific computing concepts beyond what is needed to understand the core Eigen::Tensor functionality
If you have not taken an Open Risk Academy course before the "CrashCourse Academy Demo" provides a quick overview of the Academy.
The following table places the course in the Open Risk skills diagram:
|Introductory Level||Core Level||Advanced Level|
The course material comprises the following:
- 14 interactive readings
- Embedded exercises based on the daily material
Time Requirements and Important Dates
- The course is self-paced and can be undertaken at any point. It requires a commitment of about one or two days total, depending on your familiarity with linear algebra and C++.
Where To Get Help:
If you get stuck on any issue with the course or the Academy:
- If the issue is related to the course topics / material, check in the first instance the Course Forum
- If the issue is related the operation of the Open Risk Academy check first the Academy FAQ. If the issue persists contact us at email@example.com