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A Beauty's Plan -EP 13 English SUB
⏲ 12:21 👁 100K
Toys and Colors
⏲ 19 minutes 42 seconds 👁 1.9M
Candy Land
⏲ 9 minutes 19 seconds 👁 16.7M
Supermarket staff have put up barriers and cordoned off eight parking spaces - to protect a seagull.<br/><br/>The gull is sitting on eggs in a nest it built at the base of a tree in the Morrisons car park in Liskeard, Cornwall. <br/><br/>The gull is now surrounded by barriers and staff have cordoned off eight car parking spaces to protect it.<br/><br/>The supermarket staff contacted the RSPCA for advice and were told to seal off space for the bird so they would not be disturbed.<br/><br/>All wild birds, their eggs and nests are protected by law.<br/><br/>It is an offence to damage or destroy a wild bird’s nest while it is being used or built.<br/><br/>The RSPCA added the gull could scare or hurt customers if distressed.<br/><br/>A spokesperson for Morrisons said staff contacted the RSPCA for advice and were told to cordon off space so the bird would not be disturbed.
⏲ 1:16 👁 260K
A Beauty's Plan -EP 12 English SUB
⏲ 15:21 👁 125K
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
Candy the goat had different ways of headbutting different goats. Here, Candy was playing with a senior goat and so was careful to be very gentle when headbutting them.<br/><br/>The underlying music rights are not available for license. For use of the video with the track(s) contained therein, please contact the music publisher(s) or relevant rightsholder(s).
⏲ 0:11 👁 75K
Lyrics:<br/><br/>Verse 1:<br/>Pomni: 1, 2, 3, 4<br/>Counting every day<br/>I’ve been stuck in here, can someone help me get away<br/>5, 6, 7, 8<br/>Time is just a hoax<br/>In a colored world of characters and family jokes<br/><br/>Pre Chorus 1:<br/>Caine: you must think that you’re dreaming<br/>Pomni: Just tell me what you’re scheming<br/>Caine: You look like you’ve seen a ghost<br/>You’re lucky to have such a gracious host like me<br/>Pomni: I’m scared to lose myself here<br/>Caine: But there is nothing to fear<br/>Pomni: I can’t take it anymore<br/>Is that an exit door?<br/><br/>Chorus :<br/>Just your imagination<br/>The exit is your fixation<br/>Door after door you find that it is just a digital hallucination<br/><br/>You try to find a way out<br/>But you're stuck here day after day<br/>Inside a Digital hallucination<br/><br/>Verse 2:<br/>Pomni: A, B, C, D<br/>I don’t know my name<br/>Tell me if i’m dead or if i’m just going insane<br/>X, D, D, C<br/>The writing on the wall<br/>The vowels and the consonants say “save us all”<br/><br/>Pre Chorus 2:<br/>Jax: You must think that you’re dreaming<br/>Ragatha: It'll be okay believe me<br/>Kinger: You look like you’ve seen a ghost<br/>Jax: You’re lucky to have what’s left of your sanity<br/>Gangle: And some might call it tragic<br/>Zooble: When the circus lost it’s magic<br/>Pomni: I can’t take it anymore<br/>Is that an exit door?<br/><br/>Chorus :<br/>Just your imagination<br/>The exit is your fixation<br/>Door after door you find that it is just a digital hallucination<br/><br/>You try to find a way out<br/>But you're stuck here day after day<br/>Inside a Digital hallucination<br/><br/>Bridge:<br/>Pomni: <br/>Is it an amalgamation<br/>Of my own fixation?<br/>Door after door I find that it is just a digital hallucination<br/><br/>I want to find a way out<br/>But I’m stuck here day after day<br/>Inside this Digital hallucination<br/><br/>Chorus :<br/>Just your imagination<br/>The exit is your fixation<br/>Door after door you find that it is just a digital hallucination<br/><br/>You try to find a way out<br/>But you're stuck here day after day<br/>Inside a Digital hallucination
⏲ 4:22 👁 150K
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 \
⏲ 4:28 👁 40K
Pakistani Most Famous Show Hasna Mana Hai With Tabish Hashmi<br/><br/>Follow<br/>Like<br/>Comments<br/>Share<br/><br/>Watch now
⏲ 2:21 👁 40K
My Desire candy CEO,don't underestimate me<br/>The girl married a sickly CEO forcefully, but at night she unexpectedlly discovered his secret<br/>#film#filmengsub #movieengsub #reedshort #haibarashow #3tchannel#chinesedrama #drama #cdrama #dramaengsub #englishsubstitle #chinesedramaengsub #moviehot#romance #movieengsub #reedshortfulleps<br/>TAG:3t channel, 3t channel dailymontion,drama,chinese drama,cdrama,chinese dramas,contract marriage chinese drama,chinese drama eng sub,chinese drama 2024,best chinese drama,new chinese drama,chinese drama 2024,chinese romantic drama,best chinese drama 2024,best chinese drama in 2024,chinese dramas 2024,chinese dramas in 2024,best chinese dramas 2023,chinese historical drama,chinese drama list,chinese love drama,historical chinese drama<br/>
⏲ 2:8:1 👁 185K
Lyrics:<br/><br/>One, two, three, four, counting every day<br/>I've been stuck in here, can someone help me get away?<br/>Five, six, seven, eight, time is just a hoax<br/>In a colored world of characters and family jokes<br/><br/>You must think that you're dreaming<br/>Just tell me what you're scheming<br/>You look like you've seen a ghost<br/>But you're lucky to have such a gracious host like me<br/>I'm scared to lose myself here<br/>But there is nothing to fear<br/>I can't take it anymore<br/>Is that an exit door?<br/><br/>Just your imagination<br/>The exit is your fixation<br/>Door after door, you'll find that it's just a digital hallucination<br/>You try to find a way out<br/>But you're stuck here day after day<br/>Inside a digital hallucination<br/>(Oh-oh-oh-oh-oh-oh-oh)<br/>(Oh-oh-oh-oh-oh-oh-oh)<br/><br/>A, B, C, D, I don't know my name<br/>Tell me if I'm dead, or if I'm just going insane<br/>X, D, D, C, the writing on the wall<br/>The vowels and the consonants says, \
⏲ 4:5 👁 105K
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