Merge pull request #2257 from moj-analytical-services/fix_bullets

Fix bullets in readme.md

README.md

@@ -16,11 +16,11 @@ Splink is a Python package for probabilistic record linkage (entity resolution)
 
 ## Key Features
 
-⚡ **Speed:** Capable of linking a million records on a laptop in around a minute.
-🎯 **Accuracy:** Support for term frequency adjustments and user-defined fuzzy matching logic.
-🌐 **Scalability:** Execute linkage in Python (using DuckDB) or big-data backends like AWS Athena or Spark for 100+ million records.
-🎓 **Unsupervised Learning:** No training data is required for model training.
-📊 **Interactive Outputs:** A suite of interactive visualisations help users understand their model and diagnose problems.
+⚡ **Speed:** Capable of linking a million records on a laptop in around a minute.<br>
+🎯 **Accuracy:** Support for term frequency adjustments and user-defined fuzzy matching logic.<br>
+🌐 **Scalability:** Execute linkage in Python (using DuckDB) or big-data backends like AWS Athena or Spark for 100+ million records.<br>
+🎓 **Unsupervised Learning:** No training data is required for model training.<br>
+📊 **Interactive Outputs:** A suite of interactive visualisations help users understand their model and diagnose problems.<br>
 
 Splink's linkage algorithm is based on Fellegi-Sunter's model of record linkage, with various customisations to improve accuracy.