Merge pull request #375 from ipbabble/add-mlops-fraud-detection

added a link to a demo video and some tidy up

Author: ipbabble

modules/mfd-about-mlops-fraud-detection.adoc

@@ -33,8 +33,7 @@ This architecture pattern demonstrates four strengths:
 * *Cost Efficiency*: By automating the detection process, AI reduces the need for extensive manual review of transactions, which can be time-consuming and costly.
 * *Flexibility and Agility*: An cloud native architecture that supports the use of microservices, containers, and serverless computing, allowing for more flexible and agile development and deployment of AI models. This means faster iteration and deployment of new fraud detection algorithms.
 
+== Demo Video
 
-// video link to a presentation on the use case
-.Overview of the solution in credit card fraud detection
-* video link coming soon
-// video::VHjpKIeviFE[youtube]
+.Overview of the solution for credit card fraud detection
+video::S4gVUclXlT8[youtube]

modules/mfd-architecture.adoc

@@ -19,11 +19,11 @@ Description of each component:
 image::mlops-fraud-detection/mfd-reference-architecture.png[link="/images/mlops-fraud-detection/mfd-reference-architecture.png"]
 
 //figure 2 logical
-.Logical Architecture
-//image::mlops-fraud-detection/mfd-logical-architecture-legend.png[link="/images/mlops-fraud-detection/mfd-logical-architecture-legend.png", width=940]
+//.Logical Architecture
+//image::mlops-fraud-detection/mfd-logical-architecture.png[link="/images/mlops-fraud-detection/mfd-logical-architecture.png", width=940]
 
 //figure 3 Schema
-.Data Flow Architecture
+//.Data Flow Architecture
 //image::mlops-fraud-detection/mfd-schema-dataflow.png[link="/images/mlops-fraud-detection/mfd-schema-dataflow.png", width=940]
 
 [id="about-technology"]