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<p>The Fawlty Towers star said his Monty Python pal is lovely but boring and joked his shows are used to cure insomnia.</p><br/><p>Credit: Lorraine / ITV / ITVX</p>

John Cleese calls Michael Palin's travel shows boring

⏲ 0:53 👁 2.2M

ProgramsAndMe

Printing Stars \"*\" in Pyramid Shape | Triangle | Python Pattern Program

⏲ 7 minutes 54 seconds 👁 64.4K

Telusko

#31 Python Tutorial for Beginners | Working with Matrix in Python

⏲ 11 minutes 55 seconds 👁 396.3K

This planet, Tianyuan Realm, is owned by Origin Qi and is majestic and majestic. Origin Qi has the power to shift mountains, overturn seas, overturn the sky, and rule the universe of Yin and Yang. It is an adaptation of Tiancan Tudou's novel of the same name. An enemy nation with hundreds of millions of people threatened Zhou Yuan, a young man from the Great Zhou Dynasty.The dragon was \

Dragon Prince Yuan Ep 4 ENG SUB

⏲ 18:38 👁 1.2M

shiva prasad m

Python : Transpose of a Matrix explained by shiva prasad m #matrix

⏲ 12 minutes 29 seconds 👁 692

Left Peel

Python Programming Series (Loops 4): Nested loops

⏲ 14 minutes 45 seconds 👁 82.1K

Movie Story: A usual working day turns unusual for Guru and Harini when they get trapped in their haunted office. A patterned game unlocks a mystery and a lift is their only way out.<br/><br/>

Lift (2021) UNCUT Dual Audio _Horror, Mystery

⏲ 2:14:48 👁 335K

CodingFacts

Spiral Matrix in Python | Python Program | CodingFacts

⏲ 9 minutes 19 seconds 👁 2.8K

Techdose

Trick for spiral matrix traversal

⏲ 10 minutes 12 seconds 👁 96.9K

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

[Python]Detectpattern matrix

⏲ 49 seconds 👁 67

Training2SQL MSBI

Matrix Examples in Python | printing patterns in python | python tutorials

⏲ 13 minutes 26 seconds 👁 444

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