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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

Philips

SENSEO® Original Machine à café à dosettes - FR

⏲ 45 seconds 👁 4.5K

SYSTÈME D

Dosettes café réutilisables rechargeables Senseo

⏲ 5 minutes 20 seconds 👁 11.5K

Brain-Machine Interface (BMI) Technologies: Revolutionizing Human-Technology Interaction<br/><br/>Brain-Machine Interface (BMI) technologies, championed by companies like Neuralink, are at the forefront of transforming how humans interact with technology. Founded by Elon Musk, Neuralink aims to develop sophisticated brain-computer interfaces that promise to revolutionize communication, enhance human capabilities, and push the boundaries of artificial intelligence (AI). However, as with any groundbreaking technology, BMIs come with a host of ethical, societal, and practical concerns that need careful consideration.<br/><br/>Neuralink: A Leading Player in BMI Technology<br/><br/>Neuralink stands out as a pioneer in the field of brain-machine interfaces. The company’s ambitious goals extend beyond medical applications, aspiring to enhance human capabilities and integrate AI seamlessly with human cognition. The vision includes enabling people to communicate sensations, emotions, and memories through targeted neural stimulation, potentially transforming our interaction with technology and each other.<br/><br/>Ethical Dilemmas: Privacy and Autonomy at Stake<br/><br/>The concept of merging human minds with technology raises significant ethical and societal dilemmas. One of the foremost concerns is privacy. The idea that an entity—be it a government or corporation—could access and interpret our thoughts is disconcerting. This potential for privacy breaches underscores the need for stringent ethical guidelines to govern the use of BMIs.<br/><br/>Additionally, there is the risk of manipulation. If thoughts and sensations can be influenced through BMIs, the technology could be misused to control or coerce individuals, raising questions about autonomy and consent. Establishing robust safeguards and ethical frameworks is crucial to ensure that BMI technology is used responsibly and ethically.<br/><br/>Beyond Medicine: Enhancing Human Capabilities<br/><br/>While BMIs hold promise for medical advancements, such as treating neurological disorders and physical disabilities, their potential applications extend far beyond healthcare. BMIs could pave the way for enhanced human experiences and cognitive abilities, creating immersive virtual environments and direct brain-to-brain communication.<br/><br/>Imagine a future where knowledge can be directly uploaded into the brain, revolutionizing education and skill acquisition. Or consider virtual reality experiences that are so immersive they feel as real as physical presence. These possibilities are both exciting and fraught with ethical considerations, particularly concerning dependency and the potential for misuse.<br/>

Brain-Machine Interface (BMI) Technologies

⏲ 5:48 👁 135K

CapsulCN

Semi-automatic Capsule filling machine JTJ-V Pro Drawer Typeshowcase

⏲ 1 minute 7 seconds 👁 50

Toul'événement Toulouse

Démonstration: machine Nespresso pro double

⏲ 2 minutes 37 seconds 👁 6.1K

Contagion of Fear (2024) Hindi Dubbed Movie

Contagion of Fear (2024) Hindi Dubbed Movie

⏲ 1:37:56 👁 180K

USM Fabrication

Épisode 5 : fraisage et tournage d'une bride en deux parties

⏲ 34 minutes 59 seconds 👁 33.1K

Food Story

Café Nespresso, d'où viennent vraiment les célèbres capsules ?

⏲ 27 minutes 17 seconds 👁 189.7K

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

Adventures In Odyssey video series from 1991-2003 is a Focus On The Family spin off of the radio dramas beginning in 1987.<br/><br/>This is an unofficial soundtrack for this series.<br/><br/>watch here<br/>https://rumble.com/v4qwtuz-adventures-in-odyssey-01.-the-knight-travelers-1991.html?mref=rcqv5&mc=9wzzk<br/><br/>listen here<br/>https://rumble.com/v4r0w4r-adventures-in-odyssey-01.-the-knight-travelers-1991-unofficial-soundtrack.html?mref=rcqv5&mc=9wzzk<br/><br/><br/>01. Focus On The Family 0:00<br/>02. Thieves In Rain 0:12<br/>03. AIO The Knight Travelers [Main Theme] 1:18<br/>04. Toys (It's All Mine - Greedy) 2:15<br/>05. Outside (Bored To Pieces) 3:36<br/>06. Laminate The Witness (It's A Little Kid) 3:59<br/>07. Thanks (Come Back) 4:49<br/>08. Misuse (Alter The Machine) 5:13<br/>09. Mr. Faustus (Freddy - Manipulation Station - Bernice)5:55<br/>10. Whit's End (Sherman) 8:16<br/>11. Strata-Flyer 8:47<br/>12. Mission Commence (A Trap For Whittaker) 10:57<br/>13. Foolish (It's A Trap - Lost)12:09<br/>14. The Proper Corrections (Habit Forming) 13:22<br/>15. To The Dark Ages (In The Joust) 14:28<br/>16. Homing Beacon (Action - Bernice Love) 15:51<br/>17. Helmet (No Helmet - The Treasures Of The World) 16:44<br/>18. Roller Skates (Trapped Like Rats) 19:00<br/>19. Joust (You'll Pay For Your Insolence!) 19:21<br/>20. Old Fashioned Ways (Hope) 20:39<br/>21. Return Home (His Name Is Sherman) 2130<br/>22. Where Our Treasure Is 22:37<br/>23. AIO The Knight Travelers [End Credits] 22:56<br/><br/>Total Running Time: 23:47

Adventures In Odyssey - 01. The Knight Travelers 1991 (Unofficial Soundtrack)

⏲ 24:0 👁 125K

Subscribe to DTB at http://digtb.us/subscribe<br/>Become a member (it's FREE) at https://digtb.us/signup<br/>Buy official DTB merch at http://digtb.us/merch<br/><br/>On this episode of DTB’s “Bus Invaders (Revisited)”, we take you inside the touring vehicle of the rock band, Danko Jones, while on tour with Volbeat and Spoken, back in 2013. Danko Jones is currently supporting their newest album, Electric Sounds.<br/><br/>VIDEO INFO:<br/>Film Date - April 5, 2013<br/>Location - Aragon Ballroom in Chicago, IL<br/><br/>KEEP UP WITH DANKO JONES:<br/>Facebook - https://facebook.com/dankojones<br/>Instagram - https://instagram.com/danko_jones<br/>Twitter - https://twitter.com/dankojones<br/><br/>WATCH MORE BUS INVADERS EPISODES:<br/>https://www.youtube.com/watch?v=NPwQrkP9P6I<br/>https://www.youtube.com/watch?v=vIo5Gl05wsM<br/>https://www.youtube.com/watch?v=i5GBEnuIReA<br/>https://www.youtube.com/watch?v=-SBs_6YHwbM<br/>https://www.youtube.com/watch?v=A7PXoVYZT7s<br/>https://www.youtube.com/watch?v=7tCh1ejj8wI<br/>https://www.youtube.com/watch?v=1Mup59tbHxg<br/>https://www.youtube.com/watch?v=QuqfT6h1c4A<br/>https://www.youtube.com/watch?v=h1M3aUS5BuA<br/>https://www.youtube.com/watch?v=ButpZzn2cng<br/><br/>FOLLOW US:<br/>Website/Email List - https://www.digitaltourbus.com/#/portal/signup<br/>YouTube - https://www.youtube.com/digitaltourbus<br/>Instagram - https://www.instagram.com/digitaltourbus/<br/>TikTok - https://www.tiktok.com/@digitaltourbus<br/>Facebook - https://www.facebook.com/digitaltourbus/<br/>Twitter - https://twitter.com/digitaltourbus<br/>Pinterest - https://www.pinterest.com/digitaltourbus/<br/>LinkedIn - https://www.linkedin.com/company/digital-tour-bus-llc<br/>Spotify - https://open.spotify.com/user/digitaltourbus<br/><br/>WATCH OUR DIFFERENT VIDEO SERIES:<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7_ByKsuzBlHLw8Z9vlvMHpo<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7-qmqFF3X8-CewdMmig-D2a<br/>https://youtube.com/playlist?list=PLPSOX00TLs78kkdygO4-67vxS4u5P6Qh7<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7_eKAu5-RHLaIhZD07cL_iy<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7-w9-ii7pFxKrqa3Fd6zEh3<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7_mIDoSuZmgzJTkhh522ZIE<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs78fQYYOLfFfCOFJOxTRfg-e<br/>https://www.youtube.com/playlist?list=PLB710EB72989541BB<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs795mjUgkfdK7YuWgwd5cluo<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7-9mycmBW-MljwWxKzQdQt2<br/>https://www.youtube.com/playlist?list=PLPSOX00TLs7_w6rQHnI6TBq-tjXQsQ5lt<br/><br/>VIDEO SUMMARY:<br/>00:00 Introduction<br/>00:32 Front Lounge<br/>02:05 Bunks<br/>02:17 Back Lounge<br/><br/>ABOUT DIGITAL TOUR BUS:<br/>Digital Tour Bus is your backstage pass to your favorite touring artists! With daily video releases, we cover all genres, and have had the pleasure of featuring the likes of Matchbox Twenty, Twenty One Pilots, Megadeth, Machine Gun Kelly, Papa Roach, and thousands of others, over the past 15 years. \

Danko Jones - BUS INVADERS (Revisited) Ep. 246 [2013]

⏲ 3:56 👁 40K

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