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There are just 50 days to go before the summer games begin.

The Olympic rings go up on the Eiffel Tower

⏲ 1:0 👁 2.3M

Civil Mentors

What is BIM? Understand Building Information Modeling

⏲ 7 minutes 29 seconds 👁 28.4K

Web Dev Cody

What does larger scale software development look like?

⏲ 24 minutes 15 seconds 👁 648.6K

Tight as a thread, seamless as a seal, and coupled like yin and yang, sunmao structures have provided sturdy and durable support for Chinese wooden architecture for centuries. <br/><br/>WATCH MORE: https://thestartv.com/c/news<br/>SUBSCRIBE: https://cutt.ly/TheStar<br/>LIKE: https://fb.com/TheStarOnline

Traditional Chinese craftsmanship gives sturdy support to timber-framed structures

⏲ 2:23 👁 4.2M

DistroTube

Vim And Emacs Are The Most Important Skills You Should Learn

⏲ 21 minutes 57 seconds 👁 18.1K

DamiLee

My Strategy for Developing Architectural Concepts

⏲ 15 minutes 59 seconds 👁 113.3K

EarthX Website: https://earthxmedia.com/ <br/><br/>Meet an artist who created a totally swoon-worthy sustainable home.<br/><br/>About House of What?!:<br/>Chris Grundy explores eclectic homes created from strange, recycled, and up-cycled materials!Learn how each house was transformed into a personal oasis and made from the greatest stuff on Earth!<br/> <br/>This clip comes from Season 1, Episode 3: \

Swoon Art House | House of What?! Clip | EarthX

⏲ 1:5 👁 85K

igmGuru

SAP VIM Training Videos | Opentext Vendor Invoice Management Demo Tutorial Updated [2024] by igmGuru

⏲ 25 minutes 54 seconds 👁 8.4K

pantechelearning

Day01 - Introduction, Python Installation, Syntax, variables, data types

⏲ 52 minutes 38 seconds 👁 2.3K

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

TheVimeagen

VIM APM - The Better Calculator

⏲ 51 minutes 2 seconds 👁 3.2K

ThePrimeagen

My Developer Workflow - How I use i3, tmux, and vim

⏲ 9 minutes 22 seconds 👁 208.1K

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