@minamaya6a: #♍處女座♍

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Sunday 26 September 2021 20:34:41 GMT

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مع سلامة🤣. #trnd #iraq #foryoupage #explore #اكسبلور #اكسبلورexplore #مالي_خلق_احط_هاشتاقات #فهد_نوري #fypシ #fyp #viral

مع سلامة🤣. #trnd #iraq #foryoupage #explore #اكسبلور #اكسبلورexplore #مالي_خلق_احط_هاشتاقات #فهد_نوري #fypシ #fyp #viral

#CapCut so với tháng trướt thì tháng này toai đã giảm dk 500gram😆😆

#CapCut so với tháng trướt thì tháng này toai đã giảm dk 500gram😆😆

#AI #ML #Softwareengineering #SOFTWAREENGINEER T𝐨𝐩 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐊 𝐌𝐞𝐚𝐧𝐬 𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐢𝐧𝐠 • Definition: Unsupervised algorithm to group similar data points into clusters. • Use Case: Market segmentation, image compression. • Strength: Simple, efficient with large datasets. 𝐋𝐢𝐧𝐞𝐚𝐫 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 • Definition: Predicts a continuous output based on input features. • Use Case: Price prediction, risk assessment. • Strength: Easy to implement and interpret. 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐓𝐫𝐞𝐞 • Definition: Splits data into branches to make decisions based on features. • Use Case: Customer relationship management, medical diagnosis. • Strength: Simple to understand, handles both numerical and categorical data. 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 • Definition: Predicts the probability of a binary outcome. • Use Case: Spam detection, credit scoring. • Strength: Efficient for binary classification problems. 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐕𝐞𝐜𝐭𝐨𝐫 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 (𝐒𝐕𝐌) • Definition: Finds the optimal hyperplane to classify data points. • Use Case: Text classification, image recognition. • Strength: Effective in high•dimensional spaces. 𝐍𝐚𝐢𝐯𝐞 𝐁𝐚𝐲𝐞𝐬 • Definition: Probabilistic classifier based on Bayes’ theorem. • Use Case: Email filtering, sentiment analysis. • Strength: Fast, handles large datasets well. 𝐊 𝐍𝐞𝐚𝐫𝐞𝐬𝐭 𝐍𝐞𝐢𝐠𝐡𝐛𝐨𝐫𝐬 (𝐊𝐍𝐍) • Definition: Classifies data based on the closest k training examples. • Use Case: Recommender systems, pattern recognition. • Strength: Simple, intuitive, and versatile. 𝐑𝐚𝐧𝐝𝐨𝐦 𝐅𝐨𝐫𝐞𝐬𝐭 • Definition: Ensemble method using multiple decision trees. • Use Case: Fraud detection, stock market prediction. • Strength: Reduces overfitting, improves accuracy. 𝐃𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧𝐚𝐥𝐢𝐭𝐲 𝐑𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 • Definition: Reduces the number of random variables to simplify models. • Use Case: Data visualization, noise reduction. • Strength: Improves performance and reduces computation time. ---------------------------------------------------------------------------- 𝐎𝐮𝐫 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 👉 Specialized in building the production grade LLM applications and NLP based systems 👉 Expertise to deliver the most advanced, integrated and full lifecycle of cloud solutions ---------------------------------------------------------------------------- Follow @quantumedgex-llc for more such content. #AI #ML #Softwareengineering #softwareengineer

#AI #ML #Softwareengineering #SOFTWAREENGINEER T𝐨𝐩 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 𝐋𝐞𝐚𝐫𝐧𝐢𝐧𝐠 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 𝐊 𝐌𝐞𝐚𝐧𝐬 𝐂𝐥𝐮𝐬𝐭𝐞𝐫𝐢𝐧𝐠 • Definition: Unsupervised algorithm to group similar data points into clusters. • Use Case: Market segmentation, image compression. • Strength: Simple, efficient with large datasets. 𝐋𝐢𝐧𝐞𝐚𝐫 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 • Definition: Predicts a continuous output based on input features. • Use Case: Price prediction, risk assessment. • Strength: Easy to implement and interpret. 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐓𝐫𝐞𝐞 • Definition: Splits data into branches to make decisions based on features. • Use Case: Customer relationship management, medical diagnosis. • Strength: Simple to understand, handles both numerical and categorical data. 𝐋𝐨𝐠𝐢𝐬𝐭𝐢𝐜 𝐑𝐞𝐠𝐫𝐞𝐬𝐬𝐢𝐨𝐧 • Definition: Predicts the probability of a binary outcome. • Use Case: Spam detection, credit scoring. • Strength: Efficient for binary classification problems. 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 𝐕𝐞𝐜𝐭𝐨𝐫 𝐌𝐚𝐜𝐡𝐢𝐧𝐞 (𝐒𝐕𝐌) • Definition: Finds the optimal hyperplane to classify data points. • Use Case: Text classification, image recognition. • Strength: Effective in high•dimensional spaces. 𝐍𝐚𝐢𝐯𝐞 𝐁𝐚𝐲𝐞𝐬 • Definition: Probabilistic classifier based on Bayes’ theorem. • Use Case: Email filtering, sentiment analysis. • Strength: Fast, handles large datasets well. 𝐊 𝐍𝐞𝐚𝐫𝐞𝐬𝐭 𝐍𝐞𝐢𝐠𝐡𝐛𝐨𝐫𝐬 (𝐊𝐍𝐍) • Definition: Classifies data based on the closest k training examples. • Use Case: Recommender systems, pattern recognition. • Strength: Simple, intuitive, and versatile. 𝐑𝐚𝐧𝐝𝐨𝐦 𝐅𝐨𝐫𝐞𝐬𝐭 • Definition: Ensemble method using multiple decision trees. • Use Case: Fraud detection, stock market prediction. • Strength: Reduces overfitting, improves accuracy. 𝐃𝐢𝐦𝐞𝐧𝐬𝐢𝐨𝐧𝐚𝐥𝐢𝐭𝐲 𝐑𝐞𝐝𝐮𝐜𝐭𝐢𝐨𝐧 𝐀𝐥𝐠𝐨𝐫𝐢𝐭𝐡𝐦𝐬 • Definition: Reduces the number of random variables to simplify models. • Use Case: Data visualization, noise reduction. • Strength: Improves performance and reduces computation time. ---------------------------------------------------------------------------- 𝐎𝐮𝐫 𝐒𝐞𝐫𝐯𝐢𝐜𝐞𝐬 👉 Specialized in building the production grade LLM applications and NLP based systems 👉 Expertise to deliver the most advanced, integrated and full lifecycle of cloud solutions ---------------------------------------------------------------------------- Follow @quantumedgex-llc for more such content. #AI #ML #Softwareengineering #softwareengineer

إلا عيونك انتاا دول بس اللي خدوني ♥✨#justmedo1 #mdamedo1 #تصاميم_مداميدو #شيماء_الشايب #ام_كلثوم #ياما_عيون_شغلوني #ياما_عيون_شغلوني_لاكن_ولاشغلوني #الا_عيونك_انت #الا_عيونك_انت_بس_اللي_خدوني🖤 #وبحبك_امروني #كلاسيك #الزمن_الجميل #fypege

إلا عيونك انتاا دول بس اللي خدوني ♥✨#justmedo1 #mdamedo1 #تصاميم_مداميدو #شيماء_الشايب #ام_كلثوم #ياما_عيون_شغلوني #ياما_عيون_شغلوني_لاكن_ولاشغلوني #الا_عيونك_انت #الا_عيونك_انت_بس_اللي_خدوني🖤 #وبحبك_امروني #كلاسيك #الزمن_الجميل #fypege

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