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| author | Christian Kolset <christian.kolset@gmail.com> | 2025-04-24 16:25:31 -0600 |
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| committer | Christian Kolset <christian.kolset@gmail.com> | 2025-04-24 16:25:31 -0600 |
| commit | 652f88728eb91bae1c4f30b63d1fbe60788ea938 (patch) | |
| tree | 65cfe591da183b969885e8c557b1ac5810727ec8 /tutorials/linear_regression.md | |
| parent | 42fca6122f4baf847ec2794b172abbc6a2193407 (diff) | |
Added jupyter notebook converter script. Converts markdown (.md) tutorials to jupyter notebook (.ipynb).
Diffstat (limited to 'tutorials/linear_regression.md')
| -rw-r--r-- | tutorials/linear_regression.md | 18 |
1 files changed, 0 insertions, 18 deletions
diff --git a/tutorials/linear_regression.md b/tutorials/linear_regression.md deleted file mode 100644 index b21415b..0000000 --- a/tutorials/linear_regression.md +++ /dev/null @@ -1,18 +0,0 @@ -# Linear Regression - - - -## Statical 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 - -mean = np.mean([1, 2, 3, 4, 5]) -median = np.median([1, 2, 3, 4, 5]) -std = np.std([1, 2, 3, 4, 5]) -variance = np.var([1, 2, 3, 4, 5]) -``` |
