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Sunderland's U21s players collect their runner-up medals after their Premier League 2 final against Tottenham
⏲ 0:44 👁 142.5M
Click and Collect | Screwfix
⏲ 30 seconds 👁 4.9K
Click and Collect | Screwfix
⏲ 31 seconds 👁 67.7K
Chinese craft lands on moon's far side amid global rivalry in space
⏲ 0:36 👁 17.1M
Screwfix has adapted its service to offer Click & Collect and Home Delivery.| Screwfix
⏲ 1 minute 14 seconds 👁 2K
Shopping Lanes | Screwfix
⏲ 31 seconds 👁 814
Understanding Privacy and Data Collection on WhatsApp, Facebook, and Telegram
⏲ 4:0 👁 155K
A Job Well Done - Click and Collect | Screwfix
⏲ 16 seconds 👁 684
Screwfixopen 7 daysTool shop in uk
⏲ 56 seconds 👁 318
Session 17: Deployment of Machine Learning Models in Open RAN Networks
⏲ 4:9 👁 75K
How to offer Click & Collect on your listings | eBay for Business UK
⏲ 2 minutes 55 seconds 👁 17.5K
Open 7 Days | Screwfix
⏲ 30 seconds 👁 66.1K
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_sunderland39s-u21s-players-collect-their-runner-up-medals-after-their-premier-league-2-final-against-tottenham.webp "Sunderland's U21s players collect their runner-up medals after their Premier League 2 final against Tottenham at the Tottenham Hotspur Stadium")
_click-and-collect-124-screwfix.webp "Screwfix")
_click-and-collect-124-screwfix.webp "Screwfix")
_chinese-craft-lands-on-moon39s-far-side-amid-global-rivalry-in-space.webp "The Chinese craft is now inthe South Pole-Aitken Basin and will try to collect two kilos of moon rock and debris to bring back to Earth.")
_screwfix-has-adapted-its-service-to-offer-click-amp-collect-and-home-delivery-124-screwfix.webp "Screwfix")
_shopping-lanes-124-screwfix.webp "Screwfix")
_understanding-privacy-and-data-collection-on-whatsapp-facebook-and-telegram.webp "In this comprehensive video, we dive deep into how WhatsApp, Facebook, and Telegram manage your privacy and what data they collect. With billions of users worldwide, it's crucial to understand how these popular messaging platforms ensure the security of your information. From end-to-end encryption and privacy settings to data sharing and user rights, we cover everything you need to know to protect your digital privacy. Stay informed and make educated decisions about your online communications.<br/><br/>Chapters:<br/>0:00 Introduction<br/>1:30 WhatsApp: Privacy and Data Collection<br/>12:45 Facebook: Privacy and Data Collection<br/>25:30 Telegram: Privacy and Data Collection<br/>38:00 Conclusion<br/><br/>Tags:<br/><br/>WhatsApp Privacy<br/>Facebook Privacy<br/>Telegram Privacy<br/>Data Collection<br/>End-to-End Encryption<br/>Digital Security<br/>Online Privacy<br/>Social Media Security<br/>Messaging Apps Security<br/>Data Protection<br/>WhatsApp Features<br/>Facebook Features<br/>Telegram Features<br/>Internet Safety<br/>Privacy Settings<br/>Secure Messaging<br/>Privacy Tips<br/>Meta Platforms<br/>Pavel Durov<br/>Digital Privacy 2024<br/>Viral Privacy Tips")
_a-job-well-done-click-and-collect-124-screwfix.webp "Screwfix")
_screwfix-open-7-days-tool-shop-in-uk.webp "Subharam Vlogs UK")
_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 \")
_how-to-offer-click-amp-collect-on-your-listings-124-ebay-for-business-uk.webp "eBay for Business UK")
_open-7-days-124-screwfix.webp "Screwfix")
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