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As the counting for the Lok Sabha Elections 2024 is underway, Chief Election Commissioner Rajiv Kumar is closely monitoring the process through video conferencing to ensure transparency and accuracy. Join us for real-time updates, in-depth analysis, and live coverage from various counting centres across Delhi. Stay informed about the latest developments in this crucial electoral process. <br/> <br/>#LokSabhaElections2024 #CountingDay #CECRajivKumar #ElectionUpdates #DelhiElections #VideoConferencing #ElectionCommission #Transparency #VoteCounting #IndianPolitics #BreakingNews<br/>~PR.274~ED.155~

Lok Sabha Elections 2024: CEC Rajiv Kumar Monitors Counting via Video Conferencing | Oneindia News

⏲ 3:55 👁 80K

Best Buy Canada Product Videos

KardiaMobile Personal EKG Monitors Review

⏲ 3 minutes 7 seconds 👁 21.2K

Digitize Health

AliveCor KardiaMobile 6L ECGEKG Device for Atrial Fibrillation- A Doctor's Review

⏲ 11 minutes 52 seconds 👁 78.7K

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 \

Session 17: Deployment of Machine Learning Models in Open RAN Networks

⏲ 4:9 👁 75K

RN Scrub

KardiaMobile1 Device EKG Monitor

⏲ 1 minute 39 seconds 👁 1.9K

davidgpo

Setting Up the AliveCor KardiaMobile EKG Recorder

⏲ 13 minutes 51 seconds 👁 16.4K

Ertugrul Ghazi Urdu | Episode 54 | Season 4 #shorts <br/>Ertugrul Ghazi\

Ertugrul Ghazi Urdu | Episode 54 | Season 4

⏲ 1:0 👁 70K

Tech for Senior

Protecting your heartKardiaMobile or a Smartwatch? Advice from a Physician

⏲ 12 minutes 54 seconds 👁 3.6K

Dr Boon Lim

Patient review: AliveCor's KardiaMobile ECG heart rate monitor

⏲ 3 minutes 14 seconds 👁 409

Ertugrul Ghazi\

Ertugrul Ghazi Season 5 #ertugrulghazi

⏲ 0:38 👁 55K

KOMODO

(Review) BEST ECG EKG MONITOR OF 2023 | AliveCor KardiaMobile vs Apple Watch vs AIO Smart Sleeve

⏲ 11 minutes 28 seconds 👁 4.9K

Dr. Health Gadgets

I review the KardiaMobile device sold by AliveCor

⏲ 3 minutes 16 seconds 👁 1.2K

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