The Real Relationship Between NumPy and PyTorch in Deep‑Learning Code—and How to Learn Them in the Right Order

This guide clarifies the relationship between NumPy and PyTorch for deep‑learning developers. NumPy handles CPU‑based n…

NumPy Basics for Deep Learning: +, -, *, /, **, Comparisons, sum/mean/max/min, and axis

A detailed guide to NumPy’s core operations—element‑wise arithmetic, comparisons, aggregation functions, and the `axis`…

NumPy Indexing & Slicing: Mastering Tensor Manipulation

A step-by-step guide to essential tensor indexing and slicing in NumPy and PyTorch—from 1D to 4D+—covering views vs. co…

NumPy ndarray Basics for Deep Learning Beginners: array, dtype, shape, reshape, astype

A deep dive into NumPy’s core `ndarray`: how to create arrays, set `dtype`, inspect `shape`, use `reshape`, and convert…

NumPy for Deep Learning Beginners: Why It Comes Before PyTorch

NumPy is essential for deep learning beginners because it teaches the vector and matrix operations that underlie all ne…