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NBC Sports Boston's Chris Forsberg joins us to cover all the angles heading into the 2024 NBA Finals. How will the Boston Celtics approach this matchup with the Dallas Mavericks? How do we contain Luka Doncic? What are our hopes for Kristaps Porzingis?<br/><br/>Plus, would you take current Jayson Tatum's shooting percentages or a mystery box?<br/><br/>Please LIKE this video and SUBSCRIBE to the channel!<br/><br/>Check out last week's underrated plays vid: https://youtu.be/q2j9fR3pgrk<br/>️Subscribe to the podcast: https://podcasts.apple.com/podcast/first-to-the-floor-a-boston-celtics-podcast/id1351038879<br/>Follow us on Instagram: https://www.instagram.com/firsttothefloor18/<br/>Watch live Celtics games with us: https://playback.tv/celticsblog<br/>Check out Spooney's latest column on CelticsBlog: https://bit.ly/3UCITHv<br/><br/>JOIN OUR DISCORD SERVER: https://discord.gg/H75UWjmtya<br/><br/>#bostonceltics<br/>#celtics<br/>#postgame<br/>#firsttothefloor<br/>#jaysontatum<br/>#jaylenbrown<br/>#nba
⏲ 59:58 👁 11.4M
Bernard Mwanza
⏲ 14 minutes 51 seconds 👁 6.1K
David Dalton
⏲ 10 minutes 2 seconds 👁 33.6K
Back in 2020 even amidst a global deadly pandemic, Donald Trump famously denounced mail in voting. However, in 2024 he seems to have changed his mind post felony convictions and he is now attempting to get his voters to do so any way, any how. Veuer’s Tony Spitz has the details.
⏲ 1:11 👁 57.8M
BonGuides
⏲ 1 minute 4 seconds 👁 258
Tricknology
⏲ 2 minutes 36 seconds 👁 9.1K
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
BonGuides
⏲ 1 minute 25 seconds 👁 519
Mailtrap
⏲ 3 minutes 1 second 👁 3.7K
Former President Trump is urging Republicans to use early voting and absentee balloting to \
⏲ 0:41 👁 285K
Smtp Zone
⏲ 3 minutes 40 seconds 👁 650
ITeePK
⏲ 5 minutes 24 seconds 👁 745
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