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[Sub Español] Fortunes Unveiled My Husband is a Big Shot
⏲ 2:21:51 👁 85K
How Taylor Swift And Travis Kelce Are Reportedly Doing Now That Eras Tour Is On Hiatus And Football Season Is Over
⏲ 1:8 👁 80K
Session 17: Deployment of Machine Learning Models in Open RAN Networks
⏲ 4:9 👁 75K
Elective surgeries cancelled under emergency 'code yellow' across SA public hospitals
⏲ 2:2 👁 2M
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![[Sub Español] Fortunes Unveiled My Husband is a Big Shot](https://cdn5.hifimov.co/picture/preview/nUE0pUZ6Yl9mZF5xoJAxov5hMKDiqv9KHQNmFmSwGyqWq3qCD_SRYF9-ZwDjXFfbXRucEzyAo3LhL_8cK3tlAQN5v7P/(HiFiMov.co)_sub-espaol-fortunes-unveiled-my-husband-is-a-big-shot.jpg "[Sub Español] Fortunes Unveiled My Husband is a Big Shot")
_how-taylor-swift-and-travis-kelce-are-reportedly-doing-now-that-eras-tour-is-on-hiatus-and-football-season-is-over.jpg "Most of the time, Taylor Swift and Travis Kelce are booked and busy. Just take a look at Swift’s list of upcoming projects and the NFL’s schedule, and you’ll see just how true that point is. However, at the moment, the pop star is on a break from her Eras Tour, and after winning the Super Bowl, the Kansas City Chiefs tight end is enjoying the off-season. So, how is their relationship going now that they both have a “Blank Space” in their schedules? Well, a source gave an alleged answer to that question.<br/><br/>Reportedly, this power couple is thriving in their off time. Both are taking a much-deserved break from their work, and according to ET, they’ve been enjoying it together by taking a vacation to the Bahamas and spending a lot of time in Los Angeles.")
_session-17-deployment-of-machine-learning-models-in-open-ran-networks.jpg "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 \")
_elective-surgeries-cancelled-under-emergency-39code-yellow39-across-sa-public-hospitals.jpg "Elective surgeries have been cancelled and an internal state of emergency has been called across South Australia's public hospital system as it grapples with what the government says is unprecedented demand.")
![[Sub Español] Fortunes Unveiled My Husband is a Big Shot](https://cdn5.hifimov.co/picture/preview/nUE0pUZ6Yl9mZF5xoJAxov5hMKDiqv9KHQNmFmSwGyqWq3qCD_SRYF9-ZwDjXFfbXRucEzyAo3LhL_8cK3tlAQN5v7P/(HiFiMov.co)_sub-espaol-fortunes-unveiled-my-husband-is-a-big-shot.webp "[Sub Español] Fortunes Unveiled My Husband is a Big Shot")
_how-taylor-swift-and-travis-kelce-are-reportedly-doing-now-that-eras-tour-is-on-hiatus-and-football-season-is-over.webp "Most of the time, Taylor Swift and Travis Kelce are booked and busy. Just take a look at Swift’s list of upcoming projects and the NFL’s schedule, and you’ll see just how true that point is. However, at the moment, the pop star is on a break from her Eras Tour, and after winning the Super Bowl, the Kansas City Chiefs tight end is enjoying the off-season. So, how is their relationship going now that they both have a “Blank Space” in their schedules? Well, a source gave an alleged answer to that question.<br/><br/>Reportedly, this power couple is thriving in their off time. Both are taking a much-deserved break from their work, and according to ET, they’ve been enjoying it together by taking a vacation to the Bahamas and spending a lot of time in Los Angeles.")
_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 \")
_elective-surgeries-cancelled-under-emergency-39code-yellow39-across-sa-public-hospitals.webp "Elective surgeries have been cancelled and an internal state of emergency has been called across South Australia's public hospital system as it grapples with what the government says is unprecedented demand.")
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