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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
Genevieve's Playhouse - Learning Videos for Kids
Best Peppa Pig Toy Learning Videos for Kids!
⏲ 33 minutes 17 seconds 👁 22M
Genevieve's Playhouse - Learning Videos for Kids
Peppa Pig Treasure Chests Color Learning Video for Toddlers and Kids!
⏲ 10 minutes 46 seconds 👁 32.7M
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⏲ 7:19 👁 55K
Peppa Pig - Official Channel
Come Play with Peppa: Making a Chocolate Birthday Cake with Peppa Pig | Family Kids Cartoon
⏲ 56 minutes 3 seconds 👁 25.8M
We are Kids
Peppa Pig House - Family trip to Peppa Pig Theme Park
⏲ 6 minutes 31 seconds 👁 14.2M
Welcome to Session 14 of our Open RAN series! In this session, we'll introduce supervised machine learning and its application in designing intelligent systems for Open RAN.<br/><br/><br/>Understanding Supervised Machine Learning:<br/>Supervised machine learning is a type of machine learning where the algorithm learns from labeled data. It involves training a model on a dataset that contains input-output pairs, where the input is the data and the output is the corresponding label or target variable. The algorithm learns to map inputs to outputs by finding patterns in the data. In Open RAN, supervised learning can be used for tasks such as predicting network performance based on historical data.<br/><br/>Types of Supervised Machine Learning:<br/>There are two main types of supervised machine learning: classification and regression. In classification, the algorithm learns to categorize data into predefined classes or categories. For example, it can classify network traffic into different application types (e.g., video streaming, web browsing). Regression, on the other hand, involves predicting continuous values or quantities. It is used when the output variable is a real or continuous value, such as predicting the signal strength of a network connection.<br/><br/>Binary and Multi-Class Classification:<br/>Binary classification involves categorizing data into two classes or categories. For example, it can be used to classify network traffic as either malicious or benign. Multi-class classification, on the other hand, involves categorizing data into more than two classes. It can be used to classify network traffic into multiple application types (e.g., video streaming, social media, email).<br/><br/>Regression in Machine Learning:<br/>Regression is a supervised learning technique used for predicting continuous values or quantities. It involves fitting a mathematical model to the data, which can then be used to make predictions. In Open RAN, regression can be used for tasks such as predicting network latency, throughput, or coverage based on various input variables such as network parameters, traffic patterns, and environmental conditions.<br/><br/>Subscribe to \
Session 14: Introduction to Supervised Machine Learning in Open RAN
⏲ 4:28 👁 40K
Candy POP
Bluey & Peppa Pig Beach adventure ‼️ 1 HOUR
⏲ 1 hour 4 minutes 33 seconds 👁 1.6M
Kids Toys
Peppa Pig Official Channel | Peppa Pig Toys: Making a Chocolate Birthday Cake with Peppa Pig
⏲ 56 minutes 4 seconds 👁 2.4M
[Gender]: Symphonic/Blackened Death Metal<br/>[Country]: Denmark; Copenhagen, Hovedstaden<br/>[Lyrical Themes]: Death, Apocalypse<br/>[Released]: May 24, 2024<br/>[Label]: Independent<br/><br/>[TrackList]<br/><br/>01. Spiritus Noctis. [00:00]<br/>02. Tenebrae. [01:25]<br/>03. Tragoedia In Domo Dei. [06:36]<br/>04. Intra Muros Mentis. [13:26]<br/>05. Appugno. [18:51]<br/>06. Dolorum Memoria. [24:07]<br/>07. Spiritus Diurnus. [31:16]<br/>08. Arcanum Ignis Animae. [32:44]<br/><br/>[Total Playing Time]: 37:58<br/><br/>⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧<br/><br/>[Link To Buy The CD or DIGITAL ALBUM]<br/><br/>◈Amazon: https://amzn.to/458C0AQ<br/>◈BandCamp: https://cult-of-lamentari.bandcamp.com/album/ex-umbra-in-lucem<br/>◈Apple Music: https://music.apple.com/ni/album/ex-umbra-in-lucem/1740029968<br/>◈Spotify: https://open.spotify.com/intl-es/album/2q9lIaaDVoMLLLaPDcGzUU<br/>◈Deezer: https://www.deezer.com/fr/album/570525901<br/>◈YouTube: https://www.youtube.com/@lamentari9752/<br/>◈YouTube Topic: https://www.youtube.com/channel/UCx50zVb3sfa_KQJwFdxD-Ag<br/>◈YouTube Music: https://music.youtube.com/playlist?list=OLAK5uy_n7x0uuVfrLJhj9aNW5cgDflMKd7tY_UZ8<br/><br/>--- --- --- --- --- <br/><br/>[Lamentari]<br/>lamentari.band@gmail.com<br/>https://www.facebook.com/lamentari/<br/>https://www.instagram.com/lamentari_band/<br/>https://www.metal-archives.com/bands/Lamentari/<br/><br/>⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧<br/><br/>[Invite me to a beer]<br/>[Support the promotion]<br/><br/>https://paypal.me/MetalSanctvary<br/><br/>[Metal Sanctuary Promotion]<br/>◈metalsanctvary@gmail.com<br/>◈https://linktr.ee/metalsanctuary<br/><br/>*Uploaded with permission of Lamentari.<br/><br/>⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧ ⛧<br/><br/>#symphonicblackeneddeathmetal #symphonicdeathmetal #blackeneddeathmetal #deathmetal #metal #metalpromotion #metalsanctuarypromotion #Lamentari #denmarkmetal
LAMENTARI - Ex Umbra In Lucem | 2024 | Full Album |
⏲ 38:18 👁 30K
Genevieve's Playhouse - Learning Videos for Kids
Peppa and Bluey Go to School and Camping - Learning Videos for Kids!
⏲ 32 minutes 29 seconds 👁 10.6M
Just For Kids
Peppa Pig Game | Elf On The Shelf Hiding in Snow Toys
⏲ 5 minutes 54 seconds 👁 8M
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