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Welcome back to our journey through the world of Open RAN and machine learning. In this session, In this session, we'll explore the deployment of machine learning models in Open RAN networks, focusing on practical examples and deployment strategies.<br/><br/>Deployment Example:<br/>Consider a scenario where an Open RAN operator wants to optimize resource allocation by predicting network congestion. They decide to deploy a machine learning model to predict congestion based on historical traffic data and network conditions.<br/><br/>Deployment Steps:<br/><br/>1. Data Collection and Preprocessing:<br/>The operator collects historical traffic data, including throughput, latency, and user traffic patterns.<br/>They preprocess the data to remove outliers and normalize features.<br/><br/>2. Model Development:<br/>Data scientists develop a machine learning model, such as a regression model, to predict congestion based on the collected data.<br/>They use a development environment with libraries like TensorFlow or scikit-learn for model development.<br/><br/>3. Offline Model Training and Validation (Loop 1):<br/>The model is trained on historical data using algorithms like linear regression or decision trees.<br/>Validation is done using a separate dataset to ensure the model's accuracy.<br/><br/>4. Online Model Deployment and Monitoring (Loop 2):<br/>Once validated, the model is deployed in the network's edge servers or cloud infrastructure.<br/>Real-time network data, such as current traffic conditions, is fed into the model for predictions.<br/>Model performance is monitored using metrics like prediction accuracy and latency.<br/><br/>5. Closed-Loop Automation (Loop 3):<br/>The model's predictions are used by the network's orchestration and automation tools to dynamically allocate resources.<br/>For example, if congestion is predicted in a certain area, the network can allocate additional resources or reroute traffic to avoid congestion.<br/><br/>Subscribe to \
Session 17: Deployment of Machine Learning Models in Open RAN Networks
⏲ 4:9 👁 75K
MDaemon Technologies
MDaemon Email Server Tutorial - SMTP, POP, and IMAP Settings Explained
⏲ 4 minutes 58 seconds 👁 2.1K
HAVEFUTURE.BIZ
Mdaemon email server - Part 1 - install in Windows AZURE
⏲ 7 minutes 12 seconds 👁 1.8K
Former President Trump is urging Republicans to use early voting and absentee balloting to \
Trump Launches 'Swamp The Vote USA' Initiative to Promote Early Voting to 'Beat Democrat.' Biden Notes Former Past Claims of Mail-in Voting as 'Totally Corrupt', 'Cheating' and 'Fraudulent.'
⏲ 0:41 👁 285K
MDaemon Technologies
MDaemon Email Server Feature Overview
⏲ 5 minutes 12 seconds 👁 513
Zen Software - MSP u0026 Cloud Distribution
MDaemon Mail Server - Take a Look at the Control Panel
⏲ 1 minute 37 seconds 👁 114
It turns out that a lot of famous people have names that are a bit more difficult to pronounce correctly than we thought. Coming off the news that it turns out most of us have been pronouncing Rihanna’s name wrong this whole time, it’s now come to our attention that we’ve all been getting Margot Robbie’s name wrong too. The actress says she loves hearing her name spoken in her native Australia because in America we do it differently.<br/><br/>Speaking on Australia's \
Margot Robbie Says People Back Home In Australia Pronounce Her Name Differently
⏲ 1:7 👁 335K
Tutorials-breaks
Lecture 2 Installation and config of MDaemon E-mail server easy Lecture Urdu
⏲ 11 minutes 27 seconds 👁 1.2K
MDaemon Technologies
Introduction to Different MDaemon Architectures: Direct SMTP, POP, IMAP, DomainPOP, Email Gateway
⏲ 5 minutes 40 seconds 👁 1.3K
Photos by Woking FC
Woking FC new contracts
⏲ 0:12 👁 260K
LY CHAI
130Restore mail server MDaemon
⏲ 3 minutes 48 seconds 👁 125
Digital Aloha
Synology Mail Server Setup - Complete Step-By-Step Guide
⏲ 15 minutes 28 seconds 👁 21.2K
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