This will cover some basic ML concepts around learning and learning algorithm parameters.
Fundamentals of ML
C++ for Machine Learning
Personal notes around learning AI & ML for C++. This follows the book Machine Learning with C++ by Kirill Kolodiazhnyi.
These notes are meant to be a quick reference for myself and are not meant to be a replacement for the books mentioned. If you find these notes useful, please consider buying the book to support the author.
Linear Algebra for ML
This will cover some basic linear algebra terms, concepts, and algorithms that are useful for ML.
Linear Algebra for ML :: Eigen
Eigen is a general-purpose C++ library for linear algebra. In Eigen, all matrices and vectors are objects of the Matrix template class. Vectors are a specialization of the matrix type with either one row or one column. Tensor objects do not exist in the official APIs. However, they do exist as part of submodules.
Eigen comes with predefined types for vector and matrix objects. Some examples:
Eigen::Matrix3f is a 3x3 matrix of floats.