@chwico_decor: الإبداع في الصلات المغربية 😍👌 #morocco #maroc #marocaine🇲🇦 #المغرب #صالون_مغربي_تقليدي #decor #صالون_مغربي_عصري #العرب #تقليد #explor

chwico_decor
chwico_decor
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Monday 20 June 2022 23:23:10 GMT
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mer_be0
🌿♥ :
صالون تحشم تجلس فيه😂
2022-06-21 15:36:18
842
sara5au2ky8
بنت المغرب🇲🇦 :
مشاء الله على تقاليد ديالنا 🇲🇦🖐
2022-06-21 12:31:56
437
dado49378
Da Do :
بربي بقداش
2025-06-26 12:05:22
0
zinalabrune2
❤kika❤ :
بصراحة اللهم أنت شاهد على كلامي الصالون المغربي لانقاش ولا كلام أمامه سوى روعة تحفة حتى للقمة تبارك الله عليكم🇩🇿🇩🇿🇩🇿
2022-06-22 18:34:34
239
fdwysf
🌶️ ISsø 🌶️ :
اسمها مملكة مش من فراغ تبارك الله عليهم جيراننا 🇩🇿❤️🇲🇦
2022-06-22 16:58:41
250
dtf_jeans
DTF :
شحال يعجبوني صالونات تعهم بصح ما نعرف لايخلوولادهم يقعدو فيه ولا كيما حنا تع ضياف برك 🇩🇿😂😂
2022-06-22 15:12:11
27
mooz38
mooz38 :
لوك عيسى حبيت والله حبيت😁😂
2022-06-21 00:54:47
375
luna.creations2
luna :
drapeau drapeau 🇲🇦🇲🇦🇲🇦🇲🇦
2022-06-21 17:48:23
132
bassoma888
Bassoma🐎 :
فين نقدر نلقا. الي دير ليا هاد ديزاين 🥰🥰
2022-06-21 08:22:13
23
yasmineamira17
¥@$M¡RA🌻 :
thachmi takli fih lubia u la3des
2022-07-19 11:37:15
80
ninalina1861
milola :
الأغنية شابة بزاف و الصالون المغربي تبارك الله 🇩🇿🇩🇿❤❤
2022-06-22 21:03:58
67
yousrii_gh
yousra el guazouli :
Imagínate como costará recoger eso 😂
2022-06-21 18:52:52
133
chaouia_amazighia
louna_lili :
اه وحنا فدزاير كنديو الشورى زعما حوايج لبنت للراجل ولازم salon marocain🥰❤🇲🇦🇩🇿
2022-06-22 01:11:16
31
ide_alizm
♡ 𝒁𝒂𝒉𝒓𝒂 ♡ :
عشقي الصالات المغربيه 😍❤🇩🇿
2022-06-21 22:22:54
104
nutella23316
Nutella :
صراحة احسن حاجة عندهم مشاءالله ستيل يهبل 🥰 🇩🇿🙏🏻
2022-06-21 22:53:17
20
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MLOps, short for Machine Learning Operations, is a set of practices and principles aimed at streamlining the deployment, management, and monitoring of machine learning models in production environments. It combines elements from DevOps, data engineering, and machine learning to create an efficient workflow for deploying and maintaining ML models at scale. Key components of MLOps include: 🌟 Data Management: Ensuring high-quality, clean, and relevant data is available for training and inference. 🌟 Model Development: Building and training machine learning models using appropriate algorithms and techniques. 🌟 Model Deployment: Implementing mechanisms to deploy models into production environments, either as real-time services or batch processes. 🌟 Model Monitoring: Continuously monitoring model performance, detecting anomalies, and managing model drift. 🌟 Automation: Automating repetitive tasks such as model training, testing, and deployment to increase efficiency and reduce errors. 🌟 Collaboration: Facilitating collaboration between data scientists, ML engineers, and operations teams to ensure smooth integration of ML models into production systems. 🌟 Scalability: Designing MLOps pipelines to handle large volumes of data and diverse workloads efficiently. 🌟 Security and Compliance: Implementing measures to ensure data privacy, model security, and regulatory compliance. 🌟 Feedback Loop: Establishing mechanisms to gather feedback from deployed models and iteratively improve their performance over time. 🌟 Documentation and Version Control: Maintaining clear documentation and version control for models, datasets, and code to ensure reproducibility and traceability. Overall, MLOps aims to bridge the gap between machine learning development and operations, enabling organizations to deploy and manage ML models effectively in real-world environments. By implementing MLOps practices, businesses can accelerate their machine learning initiatives, reduce time-to-market, and maximize the value derived from their data assets. Join me to explore more about DevOps, MLOps, AIOps, and all things Platform; Abdullateef Lawal 🌟 Discover Codegiant, your all-in-one DevSecOps solution. Enjoy seamless integration of development, security, and operations functionalities within a single powerful platform. Subscribe to CloudNimbus: 📚 Newsletter: https://lnkd.in/dxW4xKSU 🎬 Youtube: https://lnkd.in/de3yvQPM #mlops #devops #cloud #kubernetes
MLOps, short for Machine Learning Operations, is a set of practices and principles aimed at streamlining the deployment, management, and monitoring of machine learning models in production environments. It combines elements from DevOps, data engineering, and machine learning to create an efficient workflow for deploying and maintaining ML models at scale. Key components of MLOps include: 🌟 Data Management: Ensuring high-quality, clean, and relevant data is available for training and inference. 🌟 Model Development: Building and training machine learning models using appropriate algorithms and techniques. 🌟 Model Deployment: Implementing mechanisms to deploy models into production environments, either as real-time services or batch processes. 🌟 Model Monitoring: Continuously monitoring model performance, detecting anomalies, and managing model drift. 🌟 Automation: Automating repetitive tasks such as model training, testing, and deployment to increase efficiency and reduce errors. 🌟 Collaboration: Facilitating collaboration between data scientists, ML engineers, and operations teams to ensure smooth integration of ML models into production systems. 🌟 Scalability: Designing MLOps pipelines to handle large volumes of data and diverse workloads efficiently. 🌟 Security and Compliance: Implementing measures to ensure data privacy, model security, and regulatory compliance. 🌟 Feedback Loop: Establishing mechanisms to gather feedback from deployed models and iteratively improve their performance over time. 🌟 Documentation and Version Control: Maintaining clear documentation and version control for models, datasets, and code to ensure reproducibility and traceability. Overall, MLOps aims to bridge the gap between machine learning development and operations, enabling organizations to deploy and manage ML models effectively in real-world environments. By implementing MLOps practices, businesses can accelerate their machine learning initiatives, reduce time-to-market, and maximize the value derived from their data assets. Join me to explore more about DevOps, MLOps, AIOps, and all things Platform; Abdullateef Lawal 🌟 Discover Codegiant, your all-in-one DevSecOps solution. Enjoy seamless integration of development, security, and operations functionalities within a single powerful platform. Subscribe to CloudNimbus: 📚 Newsletter: https://lnkd.in/dxW4xKSU 🎬 Youtube: https://lnkd.in/de3yvQPM #mlops #devops #cloud #kubernetes

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