user@devops:~$ cat README.md
NumPy — Vectorized Operations with Sensors
# Description
Vectorized operations with numpy project using simulated weather sensor data from Chilean cities. Learn to create and manipulate arrays, index and slice, use vectorized operations that are 10-100x faster than pure Python, broadcast operations across different array dimensions, apply boolean masks for data filtering, and compute statistics for ML data preparation. Includes Min-Max normalization, feature engineering, and manual train/test split.
# Key features
$ Creating and manipulating numpy arrays from lists and specialized functions
$ Indexing and slicing: accessing rows, columns, and ranges
$ Vectorized operations: 10-100x faster than Python loops
$ Broadcasting: operations between arrays of different dimensions
$ Boolean masks for data filtering
$ Statistics and ML data preparation: normalization, standardization
# Gallery
# Technologies used
