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| author | Christian Kolset <christian.kolset@gmail.com> | 2025-09-18 16:41:51 -0600 |
|---|---|---|
| committer | Christian Kolset <christian.kolset@gmail.com> | 2025-09-18 16:41:51 -0600 |
| commit | ab2b98a153216af10fa71f909a346bcc83533551 (patch) | |
| tree | 7a3800e69333d7d0d528e22e453f02dd53bc2990 /tutorials/module_4 | |
| parent | b7e71424dfde2ad56c4d8baaa2350e64a0f085a7 (diff) | |
Added PDE tutorial
Diffstat (limited to 'tutorials/module_4')
| -rw-r--r-- | tutorials/module_4/3_linear_regression.md | 5 |
1 files changed, 1 insertions, 4 deletions
diff --git a/tutorials/module_4/3_linear_regression.md b/tutorials/module_4/3_linear_regression.md index 298d411..d79c639 100644 --- a/tutorials/module_4/3_linear_regression.md +++ b/tutorials/module_4/3_linear_regression.md @@ -4,12 +4,9 @@ -## Statical tools +## Statistical tools Numpy comes with some useful statistical tools that we can use to analyze our data. -### Mean -The mean is the average of a set of numbers. It is calculated by summing all the numbers and dividing by the count of numbers. - ```python import numpy as np |