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Some X-Men characters are overused, problematic, or flat out boring; find out which need to go!
⏲ 8:22 👁 2.7M
Moons Signs: All You Need To Know
⏲ 1:49 👁 330K
There seems to be a torrent of new high end road bikes coming through from the big brands, all of them promising the latest and greatest developments in speed, compliance and weight but also eachclaims to have its own special way of getting a one up on its opponents. However, when you take a closer look at the top end road bikes that are being released and their associated price tags, you have to wonder if you actually need what's being put on offer and if really, the best road bikes can actually be found for a fraction of the price.
⏲ 9:9 👁 95K
Will Freeman, Latin American Studies Fellow at the CFR, joins \
⏲ 13:56 👁 7.6M
Starmer says he would be prepared to deploy nuclear weapons if needed to defend UKSource: Reuters
⏲ 1:37 👁 33.5M
NASA Alert: नासा की जेट प्रोपल्शन प्रयोगशाला ने बताया है कि एक बस के आकार का क्षुद्रग्रह, जिसे 2024 JP1 के रूप में नामित किया गया है, एक प्रक्षेपवक्र पर है जो इसे 14,400 किलोमीटर प्रति घंटे की गति से पृथ्वी की ओर लाता है। <br/>NASA’s Jet Propulsion Laboratory has reported that a bus-sized asteroid, designated as 2024 JP1, is on a trajectory that brings it towards Earth at a speed of 14,400 kilometers per hour. <br/> <br/> <br/> <br/>#NASA #Asteroid#astronomer<br/>
⏲ 3:17 👁 4.5M
 from need for speed edge
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The Unwanted Mate (Finale)
⏲ 50:12 👁 80K
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
Sewing and suturing techniques you need-le to know about! from need for speed edge
⏲ 3:12 👁 185K
The high-speed passenger train, which hit another carrying freight in the centre of the country, belonged to the private RegioJet company.
⏲ 0:35 👁 760K
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