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_session-17-deployment-of-machine-learning-models-in-open-ran-networks.webp "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 \")
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_my-final-message-before-2024-election-results---dhruv-rathee.webp "This video is just my gratitude to all of you. I did what I could, you all did what you could. I appreciate your support. I was given threats, called all kind of names, but I was there for my country. No matter what happens tomorrow, who wins tomorrow -the fight shall continue towards this country's growth, prosperity, and wellness. Jai Hind!<br/><br/>----------------------------------------------------<br/>JOIN MY COURSES: <br/> The YouTube Blueprint Course: https://academy.dhruvrathee.com/youtube<br/><br/>✏️ Time Management and Productivity Course :https://academy.dhruvrathee.com<br/>Learn how to manage time and maximize productivity in my specialised online course. <br/><br/> Master ChatGPT - Full Course : https://academy.dhruvrathee.com/chatgpt<br/>Learn to harness the power of ChatGPT effectively and transform your life! <br/>Use GET20 for a straight up 20% discount!<br/><br/>LISTEN TO MY PODCAST: <br/> My Spotify exclusive podcast. Learn about how India works, only on Maha Bharat with Dhruv Rathee: https://spoti.fi/3IhBW51<br/><br/>FOLLOW ME ON:<br/>▶️ Main Channel: <br/><br/> / dhruvrathee<br/> Vlog Channel: <br/><br/> / dhruvratheevlogs<br/> Shorts Channel: <br/><br/> / @drshorts<br/> Instagram:<br/><br/> / dhruvrathee<br/>Twitter:<br/><br/> / dhruv_rathee<br/><br/>MY VIDEO TOPICS:<br/> Geopolitics: <br/><br/> • Geopolitics<br/> History: <br/><br/> • History Education<br/> Science: <br/><br/> • Science<br/>☠️ Mystery: <br/><br/> • Mystery Videos<br/>Finance: <br/><br/> • Financial Education<br/> Indian Current Affairs: <br/><br/> • Current Affairs (India)<br/> International Current Affairs: <br/><br/> • Current Affairs (World)<br/><br/>DOWNLOAD MY APP: <br/>Android app: https://play.google.com/store/apps/de...<br/>iOS App: https://apps.apple.com/ie/app/dhruv-r...<br/><br/>This video is made solely with the purpose of spreading awareness and educating the viewers. The information demonstrated and explained in the video are true to the best of our team’s knowledge and research. Nevertheless, if any error is committed, the same was never intended to be and is absolutely unintentional. In the event of any inadvertent error, kindly email us at contact@dhruvrathee.com (mail subject : FEEDBACK) for necessary action, to resolve any error/dispute amicably. <br/><br/>Viewer’s discretion is advised w.r.t. the products/services of the sponsors advertised on our platforms. We do not claim any responsibility in any manner whatsoever regarding the product/services provided by the sponsors.")
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