user@devops:~$ cat README.md
Linear Regression — Your First ML Model
# Description
Linear regression project with scikit-learn combining synthetic data (where the exact formula is known) and real TechStore data. Learn ML fundamentals: train/test split (80/20), training with .fit(), prediction with .predict(), coefficient interpretation, and evaluation with R², MAE, and RMSE metrics. Includes comparison between perfect data (high R²) and noisy real data (lower R²), demonstrating expected real-world behavior.
# Key features
$ Linear Regression with scikit-learn: two lines to train a model
$ Train/Test Split: 80% training, 20% testing
$ Coefficient interpretation: which features increase or decrease the target
$ Evaluation metrics: R², MAE, RMSE
$ Synthetic vs real data comparison
$ Visualization of predictions vs actual values
# Gallery
# Technologies used
