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Late finishes are 'not healthy' for players - Gauff
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10 Rarest & Most Valuable PS3 Games You Might Own
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Oneindia Exclusive: BJP Candidate Ujjwal Nikam Opens Up Why BJP Will Outshines Cong. in Maharashtra
⏲ 2:23 👁 90K
Djokovic left with serious injury concerns after Roland Garros classic
⏲ 1:26 👁 85K
ACT coronial inquest opens into Nathan Booth's death in 2019.
⏲ 1:3 👁 5.5M
New craft shop and recycling scheme opens for business
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No more 'crazy' rivalries - Sabalenka prepares for Badosa at French Open
⏲ 0:49 👁 105K
Her husband destroyed her family robbed her property and killed her. An Nuan died with hatred When she opens eyes she finds that she is still alive
⏲ 17:39 👁 605K
Session 17: Deployment of Machine Learning Models in Open RAN Networks
⏲ 4:9 👁 75K
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_late-finishes-are-39not-healthy39-for-players-gauff.jpg "Coco Gauff says that finishing matches in the early hours of the morning is not healthy for the players.")
_10-rarest-amp-most-valuable-ps3-games-you-might-own.jpg "10 Rarest & Most Valuable PS3 Games You Might Own from dighi open xujdeo")
_oneindia-exclusive-bjp-candidate-ujjwal-nikam-opens-up-why-bjp-will-outshines-cong-in-maharashtra.jpg "In this Oneindia exclusive interview, BJP candidate Ujjwal Nikam discusses why he believes the BJP will outshine Congress in Maharashtra. He shares his insights on the Modi government's bold and decisive actions, particularly their response to the 2019 Pulwama attack, and how these have resonated with him and the voters. Watch as Nikam delves into the reasons behind his support for the BJP and his vision for Mumbai North Central. <br/> <br/> <br/>#UjjwalNikam #UjjwalNikamExclusive #UjjwalNikamInterview #UjjwalNikamBJP #MumbaiNorthCentral #MaharashtraPolitics #PoonamMahajan #OneindiaExclusive<br/>~HT.99~PR.274~ED.155~")
_djokovic-left-with-serious-injury-concerns-after-roland-garros-classic.jpg "Novak Djokovic fears a knee injury means he may not be able to take any further part in the French Open")
_act-coronial-inquest-opens-into-nathan-booth39s-death-in-2019.jpg "Nathan Booth's sister, Deanne told the Canberra Times she was glad the inquest had finally opened five years after her brother went missing.")
_new-craft-shop-and-recycling-scheme-opens-for-business.jpg "New and existing crafters are invited to indulge in a new craft shop and recycling and exchange scheme.<br/><br/>")
_no-more-39crazy39-rivalries-sabalenka-prepares-for-badosa-at-french-open.jpg "Sabalenka is looking forward to facing her 'best friend' Paula Badosa in the third round at the French Open")
_her-husband-destroyed-her-family-robbed-her-property-and-killed-her-an-nuan-died-with-hatred-when-she-opens-eyes-she-fi.jpg "Her husband destroyed her family robbed her property and killed her. An Nuan died with hatred When she opens eyes she finds that she is still alive")
_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 \")
_late-finishes-are-39not-healthy39-for-players-gauff.webp "Coco Gauff says that finishing matches in the early hours of the morning is not healthy for the players.")
_10-rarest-amp-most-valuable-ps3-games-you-might-own.webp "10 Rarest & Most Valuable PS3 Games You Might Own from dighi open xujdeo")
_oneindia-exclusive-bjp-candidate-ujjwal-nikam-opens-up-why-bjp-will-outshines-cong-in-maharashtra.webp "In this Oneindia exclusive interview, BJP candidate Ujjwal Nikam discusses why he believes the BJP will outshine Congress in Maharashtra. He shares his insights on the Modi government's bold and decisive actions, particularly their response to the 2019 Pulwama attack, and how these have resonated with him and the voters. Watch as Nikam delves into the reasons behind his support for the BJP and his vision for Mumbai North Central. <br/> <br/> <br/>#UjjwalNikam #UjjwalNikamExclusive #UjjwalNikamInterview #UjjwalNikamBJP #MumbaiNorthCentral #MaharashtraPolitics #PoonamMahajan #OneindiaExclusive<br/>~HT.99~PR.274~ED.155~")
_djokovic-left-with-serious-injury-concerns-after-roland-garros-classic.webp "Novak Djokovic fears a knee injury means he may not be able to take any further part in the French Open")
_act-coronial-inquest-opens-into-nathan-booth39s-death-in-2019.webp "Nathan Booth's sister, Deanne told the Canberra Times she was glad the inquest had finally opened five years after her brother went missing.")
_new-craft-shop-and-recycling-scheme-opens-for-business.webp "New and existing crafters are invited to indulge in a new craft shop and recycling and exchange scheme.<br/><br/>")
_no-more-39crazy39-rivalries-sabalenka-prepares-for-badosa-at-french-open.webp "Sabalenka is looking forward to facing her 'best friend' Paula Badosa in the third round at the French Open")
_her-husband-destroyed-her-family-robbed-her-property-and-killed-her-an-nuan-died-with-hatred-when-she-opens-eyes-she-fi.webp "Her husband destroyed her family robbed her property and killed her. An Nuan died with hatred When she opens eyes she finds that she is still alive")
_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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