Explanation
According to the Financial Action Task Force (FATF), the use of large amounts of cash is a common method for money launderers to move illicit funds [1]. Purchasing luxury items with cash can indicate an attempt to convert illegal funds into tangible assets that can be easily resold or moved across borders. As a result, businesses that deal with luxury items are required to implement enhanced due diligence measures, including monitoring transactions involving large amounts of cash [1].
Reference: [1] Financial Action Task Force. (2013). Money Laundering & Terrorist Financing Through the Real Estate Sector. https://www.fatf-gafi.org/media/fatf/documents/reports/ML-TF-through-real-estate.pdf

Use Azure Notebooks to develop a machine learning module and deploy it to a Linux device running Azure IoT Edge.
You can use IoT Edge modules to deploy code that implements your business logic directly to your IoT Edge devices.
References:
https://docs.microsoft.com/en-us/azure/iot-edge/tutorial-deploy-machine-learning Integrate AI models into solutions Testlet 2 Overview Contoso, Ltd. has an office in New York to serve its North American customers and an office in Paris to serve its European customers.
Existing Environment
Infrastructure
Each office has a small data center that hosts Active Directory services and a few off-the-shelf software solutions used by internal users.
The network contains a single Active Directory forest that contains a single domain named contoso.com. Azure Active Directory (Azure AD) Connect is used to extend identity management to Azure.
The company has an Azure subscription. Each office has an Azure ExpressRoute connection to the subscription. The New York office connects to a virtual network hosted in the US East 2 Azure region. The Paris office connects to a virtual network hosted in the West Europe Azure region.
The New York office has an Azure Stack Development Kit (ASDK) deployment that is used for development and testing.
Current Business Model
Contoso has a web app named Bookings hosted in an App Service Environment (ASE). The ASE is in the virtual network in the East US 2 region. Contoso employees and customers use Bookings to reserve hotel rooms.
Data Environment
Bookings connects to a Microsoft SQL Server database named hotelDB in the New York office.
The database has a view named vwAvailability that consolidates columns from the tables named Hotels, Rooms, and RoomAvailability. The database contains data that was collected during the last 20 years.
Problem Statements
Contoso identifies the following issues with its current business model:
* European users report that access to Booking is slow, and they lose customers who must wait on the phone while they search for available rooms.
* Users report that Bookings was unavailable during an outage in the New York data center for more than 24 hours.
Requirements
Contoso identifies the following issues with its current business model:
* European users report that access to Bookings is slow, and they lose customers who must wait on the phone while they search for available rooms.
* Users report that Bookings was unavailable during on outage in the New York data center for more than 24 hours.
Business Goals
Contoso wants to provide a new version of the Bookings app that will provide a highly available, reliable service for booking travel packages by interacting with a chatbot named Butler.
Contoso plans to move all production workloads to the cloud.
Technical requirements
Contoso identifies the following technical requirements:
* Data scientists must test Butler by using ASDK.
* Whenever possible, solutions must minimize costs.
* Butler must greet users by name when they first connect.
* Butler must be able to handle up to 10,000 messages a day.
* Butler must recognize the users' intent based on basic utterances.
* All configurations to the Azure Bot Service must be logged centrally.
* Whenever possible, solutions must use the principle of least privilege.
* Internal users must be able to access Butler by using Microsoft Skype for Business.
* The new Bookings app must provide a user interface where users can interact with Butler.
* Users in an Azure AD group named KeyManagers must be able to manage keys for all Azure Cognitive Services.
* Butler must provide users with the ability to reserve a room, cancel a reservation, and view existing reservations.
* The new Bookings app must be available to users in North America and Europe if a single data center or Azure region fails.
* For continuous improvement, you must be able to test Butler by sending sample utterances and comparing the chatbot's responses to the actual intent.