diff --git a/README.md b/README.md
index 677e7fc0507b524646d2842ff06d9b1992ec8668..9ef633ce2c53a60da3a37ab8dbba26d0dd70c6e5 100644
--- a/README.md
+++ b/README.md
@@ -66,11 +66,11 @@ The project is organized into the following key components:
 
  - Evaluates different recommendation models using various cross-validation techniques.
 
- - Imports key packages and modules (model_selection and accuracy from Surprise).
+ - Imports key packages and modules (`model_selection` and `accuracy` from Surprise).
 
- - Adapts the load_ratings function to load data in a format compatible with Surprise.
+ - Adapts the `load_ratings` function to load data in a format compatible with Surprise.
 
- - Implements three methods of cross-validation: generate_split_predictions, generate_loo_top_n, and generate_full_top_n. 
+ - Implements three methods of cross-validation: `generate_split_predictions,` `generate_loo_top_n`, and `generate_full_top_n`. 
  
  - Introduces three new metrics: RMSE, hit rate, and novelty.
 
@@ -81,13 +81,13 @@ The project is organized into the following key components:
 
  - Analyzes a smaller version of the dataset for debugging purposes.
 
- - Similar analyses to analytics_ui.ipynb, but on a smaller scale to speed up computation time.
+ - Similar analyses to `analytics_ui.ipynb`, but on a smaller scale to speed up computation time.
 
  8. ***analytics_test.ipynb***
 
  - Analyzes a test dataset to understand algorithm behaviors during development.
 
- - Similar analyses to analytics_ui.ipynb, but on a smaller test dataset to better understand how algorithms work.
+ - Similar analyses to `analytics_ui.ipynb`, but on a smaller test dataset to better understand how algorithms work.
 
 
 ### Datasets