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Doupo Cangqiong: Nian Fan / Fights Break Sphere 5th Season<br/>After three years of not seeing each other,Xiao Yan finally met Xun'er at Jia Nan Academy. After that,they became closer and established the Stone Gate (Pan Gate). In order to continue to improve his strength and avenge him on the Misty Cloud Sect,he risked continuing to go deeper into the Qi Refining Pagoda to devour the Fallen Heart Flame.<br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/><br/>#btth<br/>#xiaoyan<br/>#battlethroughtheheavens<br/>#nianfan<br/>#fightsbreaksphere
⏲ 16:24 👁 3.4M
Believeb Music Ltd
⏲ 4 minutes 31 seconds 👁 3.4K
Views SNTv
⏲ 3 minutes 26 seconds 👁 218
Doupo Cangqiong: Nian Fan / Fights Break Sphere 5th Season / BTTH / Battle Through The Heaven /斗破苍穹年番<br/>Subtitle Arabic ,Hindi ,Indonesia ,Japanese ,Korean ,Malay ,Portuguese ,Thai ,Vietnamese ,English ,Chinese<br/><br/>After three years of not seeing each other,Xiao Yan finally met Xun'er at Jia Nan Academy. After that,they became closer and established the Stone Gate (Pan Gate). In order to continue to improve his strength and avenge him on the Misty Cloud Sect,he risked continuing to go deeper into the Qi Refining Pagoda to devour the Fallen Heart Flame<br/><br/><br/><br/>#斗破苍穹年番<br/>#btth<br/>#btth5<br/>#btthseason5<br/>#battlethroughtheheavens<br/>#battlethroughtheheaven99<br/>#btth599
⏲ 16:24 👁 2.7M
S Music Production
⏲ 4 minutes 1 second 👁 273.5K
Suna Mia Tv
⏲ 3 minutes 3 seconds 👁 3.1M
After three years of not seeing each other,Xiao Yan finally met Xun'er at Jia Nan Academy. After that,they became closer and established the Stone Gate (Pan Gate). In order to continue to improve his strength and avenge him on the Misty Cloud Sect,he risked continuing to go deeper into the Qi Refining Pagoda to devour the Fallen Heart Flame.<br/><br/><br/><br/><br/><br/><br/><br/><br/>#btth<br/>#btth5<br/>#btthseason5<br/>#battlethroughtheheavens<br/>#battlethroughtheheaven100<br/>#btth5100<br/>#battlethroughtheheaven101<br/>#btth5101
⏲ 0:54 👁 440K
SVF
⏲ 2 minutes 33 seconds 👁 15.4M
Monir Khan
⏲ 3 minutes 53 seconds 👁 194.6K
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
Rashed HD Media
⏲ 3 minutes 42 seconds 👁 2.4K
Md Aminur Hossain
⏲ 3 minutes 39 seconds 👁 33.9K
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