NumPy Lab

Setup

Section 1 — ndarray Fundamentals

Task 1.1: Array Creation & Shapes

Create a 1D array with values 0 to 99 (no loops)

Reshape arr_1d into a (10, 10) array

Create a 3D array of shape (4, 5, 3)

Create two arrays with same values but different dtypes

Compare memory usage

Create a 2D array and slice every alternate row

Modify A_slice and observe A

Create random array of size 1000

Extract values greater than mean

Replace negative values with 0 (no loops)

Create A (1000, 50) and b (50,)

Add b to each row of A

Normalize each row of A

Intentionally trigger a broadcasting error Then fix it

Create large array X of size 1,000,000

Normalize using Python loop

Normalize using vectorization

Compute pairwise Euclidean distance matrix without loops

Implement naive softmax

Fix numerical instability

Try valid and invalid matrix multiplications

Solve Ax = b and verify solution

Compare in-place vs out-of-place operations

Inspect array strides and explain

Given X (10000, 100):