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Luís Kalil – 'Boulevard' Reverse Tapping Lesson
⏲ 9:48 👁 105K
How To Get MILLIONS Fast in Bloxburg (Roblox)
⏲ 5 minutes 39 seconds 👁 670.9K
ROBLOX| BLOXBURG| Modern Family Home (part-1) | $18k
⏲ 11 minutes 11 seconds 👁 315.3K
Josh Smith - More On The Live Version Of 'Triple J Hoedown'
⏲ 3:28 👁 220K
18k No Gamepasses Modern House | Bloxburg | Speedbuild | mxsqru
⏲ 17 minutes 10 seconds 👁 3.5K
LOCATION OF THE SAFE IN THE NEW BROOKHAVEN HOUSE!
⏲ 8 minutes 15 seconds 👁 115.5K
AWESOME EVERGREEN HAIRSTYLES INSPIRATION - NEW HAIRSTYLES TUTORIALS 2024
⏲ 6:32 👁 410K
20K MODERN HOUSE | Bloxburg Tutorial With Voice
⏲ 14 minutes 14 seconds 👁 40.7K
Session 17: Deployment of Machine Learning Models in Open RAN Networks
⏲ 4:9 👁 75K
How to mount a steel cable on walls!#tutorial
⏲ 0:30 👁 3.1M
Seymour Duncan 78 Model Humbucker Review
⏲ 8:6 👁 180K
Short video 2024
⏲ 0:6 👁 690K
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_how-to-get-millions-fast-in-bloxburg-roblox.jpg "Flxral")
_lus-kalil-39boulevard39-reverse-tapping-lesson.webp "Luís Kalil stopped by Guitar World studios to give us another lesson in reverse tapping. This time for his song, \")
_how-to-get-millions-fast-in-bloxburg-roblox.webp "Flxral")
_roblox124-bloxburg124-modern-family-home-part-1-124-3618k.webp "BarbieBuilds")
_josh-smith-more-on-the-live-version-of-39triple-j-hoedown39.webp "This is the fourth instalment on the live version of Josh Smith's tune “Triple J Hoedown,” featured on his album, Live at the Spud, recorded at the infamous Baked Potato in Los Angeles. We looked at the section that precedes his guitar solo and features drummer Gary Novak and Josh freely improvising on the groove with no strict adherence to any chord progression. Here, Josh talks about what he plays in the tune’s solo section.")
_18k-no-gamepasses-modern-house-124-bloxburg-124-speedbuild-124-mxsqru.webp "mxsqru")
_location-of-the-safe-in-the-new-brookhaven-house.webp "NanndoBlox")
_awesome-evergreen-hairstyles-inspiration-new-hairstyles-tutorials-2024.webp "AWESOME HAIRSTYLES<br/>INSPIRATION - NEW HAIRSTYLES<br/>TUTORIALS 2024<br/>Music by: creatormix.com<br/><br/>hair transformations<br/>hair tutorial<br/>easy hairstyles<br/>curly hairstyles<br/>big hair<br/>how to get big hair<br/>volumized hair<br/>nail art<br/>baby girl hairstyles with hair clip<br/>volumized hair tutorial<br/>volumized half up half down<br/>beautiful hairstyles<br/>viral hairstyles<br/><br/><br/><br/><br/>#hairtransformations<br/>#hairtutorial<br/>#easyhairstyles<br/>#curlyhairstyles<br/>#bighair<br/>#howtogetbighair<br/>#volumized hair<br/>#nailart<br/>#babygirlhairstyleswithhairclip<br/>#volumizedhairtutorial<br/>#volumizedhalfuphalfdown<br/>#beautifulhairstyles<br/>#viralhairstyles<br/>#evergreen<br/><br/><br/>")
_20k-modern-house-124-bloxburg-tutorial-with-voice.webp "forresta")
_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 \")
_how-to-mount-a-steel-cable-on-walls-tutorial.webp "We all need Sturdy Support!This activity is performed by actors in a controlled environment. Please use caution if you plan to replicate.<br/>Music by Epidemic Sound: https://www.epidemicsound.com/<br/><br/>#craft #woodmood")
_seymour-duncan-78-model-humbucker-review.webp "As Guitar World Tech Editor Paul Riario explains, “In the late ‘70s, Seymour Duncan – the man – was well-known as the guy to custom-wind pickups for some noteworthy guitarists who were looking to venture beyond what was available and create their own identifiable tone and sound.\")
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