Bump pip from 25.1 to 26.0 in /who_life_expectancy

.gitignore

@@ -5,9 +5,18 @@
 __pycache__/
 *.py[cod]
 *$py.class
-
+**/checkpoints
+**/ckpt
+# *.msgpack
+# *.ckpt
+# *.npz
 # C extensions
 *.so
+
+*/data
+/drug_alcohol_relation
+*.csv
+household_power_consumption.txt
 
 *build_opencv
 *knn

amazon_sales/pyproject.toml

@@ -0,0 +1,12 @@
+[project]
+name = "amazon-sales"
+version = "0.1.0"
+description = "A data analysis project"
+authors = [{ name = "Your Name" }]
+dependencies = [
+    "jupyterlab",
+    "seaborn",
+    "pandas",
+    "numpy",
+    "scikit-learn"
+]

amazon_sales/requirements.txt

@@ -0,0 +1,10 @@
+fqdn==1.5.1
+isoduration==20.11.0
+jsonpointer==3.0.0
+jupyterlab==4.4.3
+pipdeptree==2.26.1
+scikit-learn==1.6.1
+seaborn==0.13.2
+tinycss2==1.4.0
+uri-template==1.3.0
+webcolors==24.11.1

back-propagation/data/X_test.csv

@@ -0,0 +1,39 @@
+sepal length (cm),sepal width (cm),petal length (cm),petal width (cm)
+6.2,2.8,4.8,1.8
+6.7,3.1,4.7,1.5
+5.0,3.5,1.3,0.3
+6.5,3.0,5.2,2.0
+5.7,3.0,4.2,1.2
+5.9,3.0,4.2,1.5
+4.7,3.2,1.3,0.2
+5.7,2.8,4.5,1.3
+5.5,2.4,3.8,1.1
+4.9,2.5,4.5,1.7
+4.6,3.2,1.4,0.2
+6.2,2.2,4.5,1.5
+6.9,3.2,5.7,2.3
+5.4,3.0,4.5,1.5
+4.7,3.2,1.6,0.2
+4.8,3.4,1.6,0.2
+4.9,3.1,1.5,0.1
+6.7,2.5,5.8,1.8
+5.4,3.4,1.7,0.2
+4.4,3.2,1.3,0.2
+5.8,2.7,3.9,1.2
+6.3,2.3,4.4,1.3
+4.4,3.0,1.3,0.2
+5.8,2.7,5.1,1.9
+5.0,3.6,1.4,0.2
+7.7,2.6,6.9,2.3
+6.0,3.0,4.8,1.8
+7.1,3.0,5.9,2.1
+7.7,3.8,6.7,2.2
+6.6,3.0,4.4,1.4
+6.4,3.2,5.3,2.3
+5.0,2.0,3.5,1.0
+6.0,2.2,5.0,1.5
+6.4,2.7,5.3,1.9
+6.7,3.0,5.0,1.7
+6.1,3.0,4.6,1.4
+5.6,2.8,4.9,2.0
+6.1,2.8,4.0,1.3

back-propagation/data/X_train.csv

@@ -0,0 +1,113 @@
+sepal length (cm),sepal width (cm),petal length (cm),petal width (cm)
+5.5,2.4,3.7,1.0
+4.8,3.0,1.4,0.1
+5.5,2.6,4.4,1.2
+5.0,3.2,1.2,0.2
+6.9,3.1,5.1,2.3
+5.9,3.0,5.1,1.8
+5.0,3.4,1.6,0.4
+6.6,2.9,4.6,1.3
+5.7,2.8,4.1,1.3
+5.0,2.3,3.3,1.0
+6.3,3.4,5.6,2.4
+6.0,3.4,4.5,1.6
+5.2,3.5,1.5,0.2
+5.9,3.2,4.8,1.8
+6.1,2.6,5.6,1.4
+5.6,2.7,4.2,1.3
+5.1,3.8,1.5,0.3
+7.7,2.8,6.7,2.0
+5.7,2.6,3.5,1.0
+5.2,2.7,3.9,1.4
+6.5,2.8,4.6,1.5
+6.5,3.0,5.8,2.2
+5.8,2.7,5.1,1.9
+5.5,2.5,4.0,1.3
+6.0,2.7,5.1,1.6
+5.5,4.2,1.4,0.2
+5.0,3.0,1.6,0.2
+5.6,2.5,3.9,1.1
+5.2,4.1,1.5,0.1
+6.1,2.8,4.7,1.2
+5.4,3.7,1.5,0.2
+6.5,3.2,5.1,2.0
+6.4,2.8,5.6,2.1
+4.6,3.1,1.5,0.2
+4.9,2.4,3.3,1.0
+6.3,3.3,6.0,2.5
+4.8,3.1,1.6,0.2
+5.1,3.3,1.7,0.5
+5.7,3.8,1.7,0.3
+5.7,4.4,1.5,0.4
+7.4,2.8,6.1,1.9
+6.4,2.9,4.3,1.3
+4.9,3.0,1.4,0.2
+5.1,2.5,3.0,1.1
+6.8,2.8,4.8,1.4
+6.3,3.3,4.7,1.6
+5.4,3.9,1.3,0.4
+6.0,2.2,4.0,1.0
+4.9,3.1,1.5,0.1
+6.8,3.2,5.9,2.3
+6.7,3.1,4.4,1.4
+5.7,2.9,4.2,1.3
+5.0,3.4,1.5,0.2
+5.1,3.5,1.4,0.3
+5.8,2.7,4.1,1.0
+6.2,3.4,5.4,2.3
+6.4,3.2,4.5,1.5
+6.7,3.3,5.7,2.5
+7.0,3.2,4.7,1.4
+6.3,2.9,5.6,1.8
+6.8,3.0,5.5,2.1
+5.1,3.7,1.5,0.4
+4.8,3.0,1.4,0.3
+6.7,3.1,5.6,2.4
+5.4,3.4,1.5,0.4
+6.4,3.1,5.5,1.8
+6.5,3.0,5.5,1.8
+5.6,2.9,3.6,1.3
+5.3,3.7,1.5,0.2
+5.7,2.5,5.0,2.0
+4.9,3.1,1.5,0.1
+5.4,3.9,1.7,0.4
+6.7,3.3,5.7,2.1
+6.9,3.1,4.9,1.5
+4.8,3.4,1.9,0.2
+5.6,3.0,4.5,1.5
+5.1,3.8,1.9,0.4
+4.3,3.0,1.1,0.1
+7.9,3.8,6.4,2.0
+7.6,3.0,6.6,2.1
+5.1,3.8,1.6,0.2
+7.3,2.9,6.3,1.8
+6.0,2.9,4.5,1.5
+6.1,3.0,4.9,1.8
+5.8,2.8,5.1,2.4
+4.6,3.4,1.4,0.3
+6.7,3.0,5.2,2.3
+6.4,2.8,5.6,2.2
+5.0,3.3,1.4,0.2
+5.1,3.5,1.4,0.2
+4.6,3.6,1.0,0.2
+4.4,2.9,1.4,0.2
+5.1,3.4,1.5,0.2
+5.5,3.5,1.3,0.2
+4.5,2.3,1.3,0.3
+7.2,3.6,6.1,2.5
+6.3,2.5,5.0,1.9
+5.8,2.6,4.0,1.2
+6.9,3.1,5.4,2.1
+6.3,2.8,5.1,1.5
+5.6,3.0,4.1,1.3
+6.1,2.9,4.7,1.4
+7.7,3.0,6.1,2.3
+5.5,2.3,4.0,1.3
+6.2,2.9,4.3,1.3
+5.0,3.5,1.6,0.6
+6.3,2.5,4.9,1.5
+6.3,2.7,4.9,1.8
+7.2,3.0,5.8,1.6
+5.8,4.0,1.2,0.2
+5.2,3.4,1.4,0.2
+7.2,3.2,6.0,1.8