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_kaymer-39trending-in-the-right-direction39-ahead-of-pinehurst-return.jpg "Martin Kaymer says that 'all the little things are falling into place' one week out from his Pinehurst return.")
⏲ 0:49 👁 115K
_andreeva-admits-39negative-thoughts39-take-over-after-defeat.jpg "Andreeva admits she finds it hard to get over the disappointment of losing after her defeat to Jasmine Paolini")
⏲ 0:54 👁 105K
_breaking-news-djokovic-withdraws-from-french-open.jpg "Novak Djokovic has withdrawn from this year's French Open ahead of Ruud quarter-final due to a knee injury.")
⏲ 0:42 👁 995K
_andreeva-39didn39t-expect39-to-be-in-the-french-open-semi-finals.jpg "Mirra Andreeva admits it's 'a dream' to be in the final four at Roland Garros after beating Aryna Sabalenka")
⏲ 0:55 👁 95K
_french-open-disappointment-39different39-to-us-open-defeat-zverev.jpg "Alexander Zverev says he gave everything he could against Carlos Alcaraz in the French Open final")
⏲ 0:47 👁 90K
_alcaraz-surprised-by-djokovic39s-withdrawal-from-french-open.jpg "Carlos Alcaraz says Novak Djokovic's decision to withdraw from the tournament took him by surprise")
⏲ 0:59 👁 1.3M
_39i-told-you-so39-zverev-speaks-on-out-of-court-settlement.jpg "Zverev said 'he was happy' to move on with his life following the settling of his domestic abuse case")
⏲ 1:12 👁 85K
_breaking-news-swiatek-wins-fourth-french-open.jpg "World number one Iga Swiatek has won her fourth French Open title, and fifth Grand Slam overall")
⏲ 0:42 👁 85K
_open-angle-and-closure-angle-glaucoma-yw-opthalmology.jpg "Open angle and closure angle glaucoma yw opthalmology from 12 girl open")
⏲ 1:35:41 👁 80K
_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 \")
⏲ 4:9 👁 75K
_dominant-zverev-through-to-french-open-final.jpg "Alexander Zverev produced a commanding performance against Casper Ruud to reach the French Open final")
⏲ 1:0 👁 75K
_winning-the-french-open-alcaraz39s-proudest-achievement.jpg "Carlos Alcaraz says winning the French Open against Alexander Zvererv is his proudest achievement in tennis")
⏲ 1:40 👁 70K
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_kaymer-39trending-in-the-right-direction39-ahead-of-pinehurst-return.webp "Martin Kaymer says that 'all the little things are falling into place' one week out from his Pinehurst return.")
_andreeva-admits-39negative-thoughts39-take-over-after-defeat.webp "Andreeva admits she finds it hard to get over the disappointment of losing after her defeat to Jasmine Paolini")
_breaking-news-djokovic-withdraws-from-french-open.webp "Novak Djokovic has withdrawn from this year's French Open ahead of Ruud quarter-final due to a knee injury.")
_andreeva-39didn39t-expect39-to-be-in-the-french-open-semi-finals.webp "Mirra Andreeva admits it's 'a dream' to be in the final four at Roland Garros after beating Aryna Sabalenka")
_french-open-disappointment-39different39-to-us-open-defeat-zverev.webp "Alexander Zverev says he gave everything he could against Carlos Alcaraz in the French Open final")
_alcaraz-surprised-by-djokovic39s-withdrawal-from-french-open.webp "Carlos Alcaraz says Novak Djokovic's decision to withdraw from the tournament took him by surprise")
_39i-told-you-so39-zverev-speaks-on-out-of-court-settlement.webp "Zverev said 'he was happy' to move on with his life following the settling of his domestic abuse case")
_breaking-news-swiatek-wins-fourth-french-open.webp "World number one Iga Swiatek has won her fourth French Open title, and fifth Grand Slam overall")
_open-angle-and-closure-angle-glaucoma-yw-opthalmology.webp "Open angle and closure angle glaucoma yw opthalmology from 12 girl open")
_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 \")
_dominant-zverev-through-to-french-open-final.webp "Alexander Zverev produced a commanding performance against Casper Ruud to reach the French Open final")
_winning-the-french-open-alcaraz39s-proudest-achievement.webp "Carlos Alcaraz says winning the French Open against Alexander Zvererv is his proudest achievement in tennis")
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