Real-world situations are greatly influenced by linear algebra, a field of mathematics that is frequently thought of as theoretical and abstract. Its real-world applications are numerous and revolutionary, ranging from robotics and quantum physics to data science and computer graphics. The complexity of linear algebra becomes more understandable and useful in a variety of contexts with ChatGPT's help.
Here are prompts for reference;

  1. I am a data science student preparing for a project involving matrix transformations. Please help in understanding and applying linear algebra concepts to real-world data analysis scenarios.
  2. As a machine learning enthusiast, I am keen to dive into the mathematics behind neural networks, which involve matrix multiplication, backpropagation, and eigenvectors. Please help me in mastering these linear algebra concepts for understanding advanced machine learning models.
  3. As a computer graphics enthusiast, I am eager to learn about 3D transformations and transformations of vectors. Please help me grasp the intricacies of linear algebra and its applications in creating lifelike graphics.

Here is the result generated by ChatGPT;