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_dolphins-v-raiders-highlights-footage-nrl-com.webp "Highlights from the Raiders' thrilling golden-point win over the Dolphins at Redcliffe on June 1. Jordan Rapana slotted two field goals to win the round 13 clash for the Green Machine. Footage: NRL.com")
_testing-a-sex-machine124-sinloli.webp "Ashley Elizabeth")
_new-arrival-venus-dildo.webp "Acmejoy Store")
_megan-fox-124-would-you-wear-it-now-124-who-what-wear.webp "Megan Fox takes a walk down fashion memory lane and plays a game of Would You Wear It Now? From the iconic fashion in Jennifer's Body to some of her most recent looks with Machine Gun Kelly, you won't want to miss this fashion time capsule.")
_my-first-sex-machine-jessky-sex-toy-review.webp "A Seijaku Life")
_atomstack-cambrian-adult-toy.webp "ATOMSTACK")
_new-cafe-with-sea-views-now-open-on-newbiggin-by-the-sea-promenade.webp "A new cafe and bistro on the Newbiggin-by-the-Sea promenade has had a busy opening week.<br/>Cafe Needles Eye, at the west end of the promenade near the Milburn Park playground and its namesake rock formation, has had to install an additional coffee machine to keep up with demand that exceeded expectations.<br/>")
_leten-king-pro-fully-automatic-sucking-male-masturbator.webp "Honeysx")
_see-how-dildos-are-made-crazy-pipedream-products-sex-toy-manufacturing.webp "Pleasure Cartel")
⏲ 2 minutes 31 seconds 👁 232.1K
_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 \")
_doing-it-the-best-sex-toys-to-help-you-squirt.webp "Adulttoymegastore")
_twitch-streamer-pulls-out-a-dildo-on-stream-ups-wrong-drawer.webp "Twitch Clips")
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