_maria-sharapova-shows-off-her-football-skills-124-fed-cup-124-itf-preview-1.jpg "Maria Sharapova Shows Off Her Football Skills! | Fed Cup | ITF from fed football Video Screenshot Preview 1")
Gallery_maria-sharapova-shows-off-her-football-skills-124-fed-cup-124-itf-preview-3.jpg "Maria Sharapova Shows Off Her Football Skills! | Fed Cup | ITF from fed football Video Screenshot Preview 3")
Gallery_maria-sharapova-shows-off-her-football-skills-124-fed-cup-124-itf-preview-hqdefault.jpg "Maria Sharapova Shows Off Her Football Skills! | Fed Cup | ITF from fed football Video Screenshot Preview hqdefault")
GalleryPlay Video:
(Note: The default playback of the video is HD VERSION. If your browser is buffering the video slowly, please play the REGULAR MP4 VERSION or Open The Video below for better experience. Thank you!)
Jump To Video Parts
⏲ Duration: 45 seconds
👁 View: 333.6K times
Play Audio:👁 View: 333.6K times
Description:
International Tennis Federation
International Tennis Federation
Share with your friends:
Whatsapp | Viber | Telegram | Line | SMS
Email | Twitter | Reddit | Tumblr | Pinterest
Related Videos
_adelaide-v-richmond-highlights-124-round-12-2024-124-afl.webp "AFL")
_fed39s-neel-kashkari-advocates-for-no-interest-rate-cut-until-39we-get-a-lot-more-data-to-convince-us39-amid-inflation-u.webp "Neel Kashkari, President of the Federal Reserve Bank of Minneapolis, has advocated for keeping interest rates unchanged until more data shows underlying inflation is declining. Kashkari believes cutting rates now could jeopardize the foundation of U.S. economic prosperity by undermining anchored inflation expectations. Kashkari does not have a vote on the FOMC this year but highlights the Fed's concerns about cutting rates prematurely before taming inflation. Kashkari says Fed should leave rates unchanged \")
_huge-recruiting-weekend-for-fsu-football.webp "FSU Football: Doak Talk")
_colorado-summer-workout-analysis-the-trenches-putting-in-work.webp "BuffsNation Daily")
_court-of-public-opinion.webp "Al Reynolds")
_not-the-sendoff-they-had-planned-reaction-to-englands-loss-to-iceland-124-espn-fc.webp "ESPN FC")
⏲ 20 minutes 58 seconds 👁 12.1K
_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 \")
_reaction-as-england-lose-to-iceland.webp "Sky Sports Football")
_adelaide-v-richmond-highlights-124-round-12-2024-124-afl.jpg)
_fed39s-neel-kashkari-advocates-for-no-interest-rate-cut-until-39we-get-a-lot-more-data-to-convince-us39-amid-inflation-u.jpg)
_huge-recruiting-weekend-for-fsu-football.jpg)
_colorado-summer-workout-analysis-the-trenches-putting-in-work.jpg)
_court-of-public-opinion.jpg)
_not-the-sendoff-they-had-planned-reaction-to-englands-loss-to-iceland-124-espn-fc.jpg)
_session-17-deployment-of-machine-learning-models-in-open-ran-networks.jpg)
_reaction-as-england-lose-to-iceland.jpg)
![[+]](/images/menu.gif){kind=small}