GateXAIML / Recommended Books
Linear Algebra
Why this subject matters: Every neural network is, underneath, a sequence of matrix multiplications — eigenvectors, singular value decomposition, and vector spaces show up constantly in ML interviews and in GATE. It is one of the highest-leverage subjects to actually understand rather than memorize.
Standard reference
Linear Algebra and Its Applications
Strang's explanations are famous for being intuitive without losing rigor — this is usually the first book recommended for building real understanding.
In-depth
Linear Algebra Done Right
A more rigorous, proof-first treatment for students who want to go beyond computation into why the theorems are true — great once the basics are solid.
Practice & problems
Schaum's Outline of Linear Algebra
A large bank of solved problems, ideal for the final weeks of revision before GATE.
