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_youtube-delete-bado-badi-song-after-28-million-views-actress-wajdan-rao-shocking-reaction-viral.webp "Bado Badi Song : सोशल मीडिया पर एक गाना 'आये हाय ओये होये' काफी ट्रेंड कर रहा है. लोगों को इसमें न सुर दिख रहा, न ताल. बावजूद इसके ये काफी ट्रेंड में है. इंस्टाग्राम पर इसके तमाम रील्स, मीम्स बन रहे हैं. इसमें एक शख्स के साथ एक लड़की को देखा जा सकता है. दोनों गाने पर थिरक रहे हैं. लेकिन अब ये सांग यू ट्यूब ने डिलीट करदिया है। <br/>Bado Badi Song: A song 'Aaye Haye Oye Hoye' is trending a lot on social media. People could see neither tune nor rhythm in it. Despite this, it is quite in trend. Many reels and memes are being made on Instagram. In this, a girl can be seen with a man. Both are dancing to the song. But now YouTube has deleted this song. <br/> <br/> <br/>#BadoBadiSong#chahtfatehalikhan #pakistaninews <br/><br/>~HT.318~PR.115~ED.284~")
⏲ 3:2 👁 2.8M
_teen-models-2007-valerie.webp "Manny De Guzman, Jr.")
_8-controversial-young-models.webp "super slideshow")
_top-10-dark-truths-about-america39s-next-top-model.webp "There are a lot of dark truths on the runway. Welcome to MsMojo, and today we’re counting down our picks for the most disturbing and shocking things about Tyra Banks’ modeling competition.")
_hot-asmr-bts-viral-model-sexy-trending-beautiful-dance.webp "#Hot #Asmr #BTS #Viral #Model #Sexy #Trending #Beautiful #Dance")
_fated-to-my-cruel-ceo-nova-media.webp "Fated To My Cruel CEO")
_skincare-tips-and-makeup-prep-with-model-pritika-swarup-124-my-five-minute-face-124-marie-claire.webp "Model and skincare entrepreneur, Pritika Swarup is the ultimate multi-hyphenate woman on the go. Embodying her effortlessly cool style and traditional ayurvedic beauty treatments, Pritika teaches us how to capture that clean girl look in just five minutes!")
⏲ 7:58 👁 6M
_vice-ganda-at-rayver-cruz-kabilang-sa-nag-model-sa-fashion-show-ni-bang-pineda-124-balitanghali.webp "Balitanghali is the daily noontime newscast of GTV anchored by Raffy Tima and Connie Sison. It airs Mondays to Fridays at 10:00 AM (PHL Time). For more videos from Balitanghali, visit http://www.gmanews.tv/balitanghali.<br/><br/>#GMAIntegratedNews #KapusoStream<br/><br/>Breaking news and stories from the Philippines and abroad:<br/>GMA Integrated News Portal: http://www.gmanews.tv<br/>Facebook: http://www.facebook.com/gmanews<br/>TikTok: https://www.tiktok.com/@gmanews<br/>Twitter: http://www.twitter.com/gmanews<br/>Instagram: http://www.instagram.com/gmanews<br/><br/>GMA Network Kapuso programs on GMA Pinoy TV: https://gmapinoytv.com/subscribe")
⏲ 1:34 👁 265K
_4k-transparent-124-windows-cleaning-124-see-through-lingerie.webp "4k Transparent | Windows Cleaning | See-Through Lingerie<br/><br/>Subscribe & Like for more Transparent Cleaning & Try On Haul videos")
_nije-sve-u-lovi-124-not-all-about-the-money.webp "Nije sve u lovi | Not All About the Money from xxxvdionarcia nn model")
_hitep9-spoiled-by-my-disabled-ceo-drama-miniseries-minidrama-revenge-minidrama-relationship.webp "HITEP9 Spoiled By My Disabled CEO drama miniseries minidrama revenge minidrama relationship")
⏲ 0:59 👁 155K
_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 \")
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