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Investors who witnessed the meteoric rise coinciding with the Model Y launch in early 2020 have largely held on despite the recent downturn. Out of 32 analysts, 9 recommend buying Tesla, 14 hold neutral ratings, and only 9 recommend selling, according to TipRanks.
Cult Of Tesla Crumbling: Early 'Die-Hard' Backers Bail As Musk's EV Empire Faces Reality Check Amid Stock Slump
⏲ 0:54 👁 515K
Dr. H Studio
Snake 3d Modelling for Animation - Tutorial | Blender ✍🏻🎧🧘🏻‍♂️
⏲ 26 minutes 32 seconds 👁 4K
DarkEdgeTV
Garden Snake SCULPTING - ZBrushCore SpeedSculpt
⏲ 18 minutes 12 seconds 👁 29.4K
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
Emz Odd Works
GIANT PYTHON SNAKE Hunts Florida Swamps, Diorama, Resin, Polymer Clay
⏲ 10 minutes 37 seconds 👁 4.1M
A+Start
Snake - Low Poly (Evolution of Characters in Games) - Episode 9
⏲ 14 minutes 36 seconds 👁 46.6K
MEGASNAKE 2 - English Movie Latest Hollywood Snake Action Adventure English Movie Chinese Movies from snake model
MEGASNAKE 2 - English Movie Latest Hollywood Snake Action Adventure English Movie Chinese Movies
⏲ 1:33:1 👁 75K
The Creative Collector
G.I. JOE Snake Eyes 3D PRINTED & Painted Resin Statue Model
⏲ 20 minutes 32 seconds 👁 4.7K
123 Easy Paper Crafts DIY
Amazing Paper Snake | Moving paper toys | Easy paper crafts
⏲ 4 minutes 10 seconds 👁 123.9K
Snake Rescue UWS
Snake Rescue UWS
⏲ 0:33 👁 1M
karrina calbrassa
Rick “The Model” Martel vsJake “The Snake” Roberts01 29 91
⏲ 12 minutes 31 seconds 👁 4.1K
Blender Default Cube
Realistic Snake Scales Modeling(use curve and array addon) in Blender 2.93
⏲ 8 minutes 40 seconds 👁 16.1K
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