What are the mathematical requirements needed to get into neural networks?
user
The mathematical requirements to get into neural networks would likely include advanced algebra, trigonometry, linear algebra, and calculus at minimum.
assistant
Why is trigonometry useful to get into neural nets?
user
Trigonometry is not a necessary component for understanding or building neural networks, but it can be useful in some applications that involve neural networks. Here are a few ways in which trigonometry can be used in the context of neural networks:

Data normalization: Trigonometric functions, such as sine and cosine, can be used to normalize data and map it to a range between -1 and 1. Normalizing data can help improve the performance of a neural network by making the optimization process easier and faster.

Activation functions: Some activation functions used in neural networks, such as the hyperbolic tangent (tanh) function, are based on trigonometric functions. These functions help to introduce non-linearities into the network and allow it to learn complex relationships between input and output.

Image processing: In some image processing tasks, such as object detection and image classification, trigonometry can be used to represent the orientation and position of objects in an image. For example, the HOG (Histogram of Oriented Gradients) descriptor, a popular feature extraction method used in object detection, makes use of trigonometry to represent the orientation of edges in an image.

In summary, while trigonometry is not a fundamental component of neural networks, it can be useful in some applications where the network needs to process data with geometric or cyclic patterns.
assistant
I've never heard of HOG. Can you explain it?
user