Add suggested workflow for data version control.

Author: Shuyib

codegotllama.txt

@@ -0,0 +1,34 @@
+# Eda-regression Makefile
+
+# Define variables
+DATA_FILE = eda-regression.csv
+OUTPUT_DIR = output/
+MODEL_OUTPUT = model_output/
+
+# Step 1: Import data
+import-data:
+    aws s3 cp s3://your-bucket-name/$DATA_FILE $OUTPUT_DIR
+    gzip -d $OUTPUT_DIR$DATA_FILE.gz
+
+# Step 2: Clean data (e.g. handle missing values, convert datatypes)
+clean-data: import-data
+    python clean_data.py $OUTPUT_DIR$DATA_FILE
+
+# Step 3: Explore data using EDA tools (e.g. correlation matrix, histograms)
+eda:
+    python eda.py $OUTPUT_DIR$DATA_FILE
+
+# Step 4: Split data into training and testing sets
+split-data: clean-data eda
+    python split_data.py $OUTPUT_DIR$DATA_FILE 0.8
+
+# Step 5: Train a machine learning model (e.g. linear regression)
+train-model: split-data
+    python train_model.py $OUTPUT_DIR$DATA_FILE.split 0.2
+
+# Step 6: Evaluate the trained model using metrics (e.g. mean squared error)
+evaluate-model: train-model
+    python evaluate_model.py $OUTPUT_DIR$MODEL_OUTPUT/model.pkl
+
+# Default target (runs all steps)
+default: import-data clean-data eda split-data train-model evaluate-model