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| author | Christian Kolset <christian.kolset@gmail.com> | 2025-05-09 09:54:05 -0600 |
|---|---|---|
| committer | Christian Kolset <christian.kolset@gmail.com> | 2025-05-09 09:54:05 -0600 |
| commit | c803df9bf08cee7f7af2ecffcc0e951325abe542 (patch) | |
| tree | 00fea936c8767683d77434edd58682eedad328f2 /tutorials/module_4 | |
| parent | 0d4e770dc06763d225dce66f82bd49b052bead06 (diff) | |
Added mod. 4 auto-gen notebooks
Diffstat (limited to 'tutorials/module_4')
| -rw-r--r-- | tutorials/module_4/notebook_4/linear_regression.ipynb | 34 |
1 files changed, 34 insertions, 0 deletions
diff --git a/tutorials/module_4/notebook_4/linear_regression.ipynb b/tutorials/module_4/notebook_4/linear_regression.ipynb new file mode 100644 index 0000000..b2d8b37 --- /dev/null +++ b/tutorials/module_4/notebook_4/linear_regression.ipynb @@ -0,0 +1,34 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Linear Regression\n", + "\n", + "## Statical tools\n", + "\n", + "Numpy comes with some useful statistical tools that we can use to\n", + "analyze our data.\n", + "\n", + "### Mean\n", + "\n", + "The mean is the average of a set of numbers. It is calculated by summing\n", + "all the numbers and dividing by the count of numbers.\n", + "\n", + "``` python\n", + "import numpy as np\n", + "\n", + "mean = np.mean([1, 2, 3, 4, 5])\n", + "median = np.median([1, 2, 3, 4, 5])\n", + "std = np.std([1, 2, 3, 4, 5])\n", + "variance = np.var([1, 2, 3, 4, 5])\n", + "```" + ], + "id": "b53d7ecf-fc41-4a2b-9d08-c38af2507843" + } + ], + "nbformat": 4, + "nbformat_minor": 5, + "metadata": {} +} |
