[pull] master from collabnix:master

Tutorials/Dockerfile

@@ -0,0 +1,27 @@
+# Python base image 
+
+FROM python:3.9-slim 
+
+
+
+# Set the working directory inside the container 
+
+WORKDIR /app 
+
+
+
+# Copy the Python script into the container 
+
+COPY code_1.py . 
+
+
+
+# Install any necessary dependencies 
+
+RUN pip install pandas matplotlib scikit-learn 
+
+
+
+# Command to run the Python script when the container starts 
+
+CMD ["python", "code_1.py"] 

Tutorials/intro_1.py

@@ -0,0 +1,65 @@
+import pandas as pd 
+
+import matplotlib.pyplot as plt 
+
+from sklearn.datasets import load_iris 
+
+from sklearn.model_selection import train_test_split 
+
+from sklearn.ensemble import RandomForestClassifier 
+
+from sklearn.metrics import accuracy_score 
+
+
+
+# Load the Iris dataset 
+
+iris = load_iris() 
+
+data = pd.DataFrame(data=iris.data, columns=iris.feature_names) 
+
+target = pd.Series(data=iris.target) 
+
+
+
+# Data Exploration 
+
+print("Dataset Description:") 
+
+print(data.describe()) 
+
+
+
+# Data Visualization 
+
+data.plot(kind='box', subplots=True, layout=(2, 2), sharex=False, sharey=False) 
+
+plt.show() 
+
+
+
+# Train-test split 
+
+X_train, X_test, y_train, y_test = train_test_split(data, target, test_size=0.2, random_state=42) 
+
+
+
+# Train a Random Forest Classifier 
+
+rf_classifier = RandomForestClassifier(n_estimators=100, random_state=42) 
+
+rf_classifier.fit(X_train, y_train) 
+
+
+
+# Make predictions 
+
+y_pred = rf_classifier.predict(X_test) 
+
+
+
+# Calculate accuracy 
+
+accuracy = accuracy_score(y_test, y_pred) 
+
+print("Accuracy:", accuracy) 

Tutorials/step3tostep7.txt

@@ -0,0 +1,10 @@
+docker build -t data_science_image . 
+docker run -it data_science_image 
+docker build -t myimage:1.0
+python  script_1.py 
+docker exec -it <container_name> python /path/to/code_1.py
+docker login 
+docker tag data_science_image collabnix12/data_science_image:v1.0 
+docker push collabnix12/data_science_image:v1.0 
+docker pull collabnix12/data_science_image:v1.0 
+docker run -it collabnix12/data_science_image:v1.0 

presentation/docker_workshop_1.html

@@ -946,7 +946,7 @@ <h2> 8.Managing Docker containers </h2>
 
 	</section>
 	<section>
-		<p> Show all the containers (includind non running containers): </p>
+		<p> Show all the containers (including non running containers): </p>
 		<pre><code class="hljs" data-trim contenteditable>
 docker ps -a 
 	 </code></pre>