{"id":252736,"date":"2025-11-27T06:38:52","date_gmt":"2025-11-27T07:38:52","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/supercourse-0000006180\/"},"modified":"2025-12-22T11:13:48","modified_gmt":"2025-12-22T12:13:48","slug":"supercourse-0000006180","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/supercourse-0000006180\/","title":{"rendered":"\u06a9\u062a\u0627\u0628 Google Cloud Platform: Natural Language Processing Application Development for Sentiment Analysis at Scale, High Accuracy, and Complexity"},"content":{"rendered":"
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\ud83c\udf93 \u062f\u0648\u0631\u0647 \u0622\u0645\u0648\u0632\u0634\u06cc \u062c\u0627\u0645\u0639<\/h2>\n<\/p><\/div>\n
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\ud83d\udcda \u0627\u0637\u0644\u0627\u0639\u0627\u062a \u062f\u0648\u0631\u0647<\/h3>\n

\u0639\u0646\u0648\u0627\u0646 \u062f\u0648\u0631\u0647:<\/strong> Google Cloud Platform: Natural Language Processing Application Development for Sentiment Analysis at Scale, High Accuracy, and Complexity<\/p>\n

\u0645\u0648\u0636\u0648\u0639 \u06a9\u0644\u06cc:<\/strong> \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc<\/p>\n

\u0645\u0648\u0636\u0648\u0639 \u0645\u06cc\u0627\u0646\u06cc:<\/strong> Google Cloud Platform (GCP)<\/p>\n<\/div>\n

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\ud83d\udccb \u0633\u0631\u0641\u0635\u0644\u200c\u0647\u0627\u06cc \u062f\u0648\u0631\u0647 (100 \u0645\u0648\u0636\u0648\u0639)<\/h3>\n
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  • \n 1.<\/span> Google Cloud Platform: Natural Language Processing Application Development for Sentiment Analysis at Scale, High Accuracy, and Complexity\n <\/li>\n
  • \n 2.<\/span> Welcome to Google Cloud NLP for Sentiment Analysis\n <\/li>\n
  • \n 3.<\/span> Course Objectives and Learning Path\n <\/li>\n
  • \n 4.<\/span> Understanding Natural Language Processing (NLP) Fundamentals\n <\/li>\n
  • \n 5.<\/span> Introduction to Sentiment Analysis: Concepts and Challenges\n <\/li>\n
  • \n 6.<\/span> Why Google Cloud Platform (GCP) for Scalable NLP?\n <\/li>\n
  • \n 7.<\/span> Setting Up Your GCP Project and Environment\n <\/li>\n
  • \n 8.<\/span> IAM: Managing Permissions and Security on GCP for ML Workloads\n <\/li>\n
  • \n 9.<\/span> GCP Core Services Overview: Compute, Storage, Networking Essentials\n <\/li>\n
  • \n 10.<\/span> Introduction to Cloud Storage for Text Data Management\n <\/li>\n
  • \n 11.<\/span> Organizing and Versioning Large Text Datasets in Cloud Storage\n <\/li>\n
  • \n 12.<\/span> Python Client Libraries for Interacting with GCP Services\n <\/li>\n
  • \n 13.<\/span> Fundamentals of Text Preprocessing: Tokenization\n <\/li>\n
  • \n 14.<\/span> Text Preprocessing: Stemming and Lemmatization Techniques\n <\/li>\n
  • \n 15.<\/span> Handling Stop Words, Punctuation, and Special Characters in Text\n <\/li>\n
  • \n 16.<\/span> Advanced Text Normalization and Cleaning Strategies\n <\/li>\n
  • \n 17.<\/span> Introduction to Feature Extraction for Text Data\n <\/li>\n
  • \n 18.<\/span> TF-IDF: Term Frequency-Inverse Document Frequency for Text Representation\n <\/li>\n
  • \n 19.<\/span> Understanding Word Embeddings: Word2Vec Principles\n <\/li>\n
  • \n 20.<\/span> Advanced Word Embeddings: GloVe and FastText\n <\/li>\n
  • \n 21.<\/span> Introduction to Contextual Embeddings: BERT Architecture\n <\/li>\n
  • \n 22.<\/span> Overview of the Cloud Natural Language API\n <\/li>\n
  • \n 23.<\/span> Performing Sentiment Analysis with the Cloud Natural Language API\n <\/li>\n
  • \n 24.<\/span> Entity Recognition and Extraction with Cloud Natural Language API\n <\/li>\n
  • \n 25.<\/span> Syntax Analysis and Parts-of-Speech Tagging with Cloud Natural Language API\n <\/li>\n
  • \n 26.<\/span> Content Classification and Categorization with Cloud Natural Language API\n <\/li>\n
  • \n 27.<\/span> Custom Entity Extraction and Annotation with Cloud Natural Language API\n <\/li>\n
  • \n 28.<\/span> Integrating Cloud Natural Language API into Python Applications\n <\/li>\n
  • \n 29.<\/span> Batch Processing Large Text Volumes with Cloud Natural Language API\n <\/li>\n
  • \n 30.<\/span> Real-time Sentiment Analysis using Cloud Natural Language API\n <\/li>\n
  • \n 31.<\/span> Monitoring and Cost Management for Cloud Natural Language API Usage\n <\/li>\n
  • \n 32.<\/span> Introduction to Data Ingestion Strategies for NLP on GCP\n <\/li>\n
  • \n 33.<\/span> Using Cloud Pub\/Sub for Real-time Streaming of Text Data\n <\/li>\n
  • \n 34.<\/span> Building Scalable ETL Pipelines with Apache Beam and Dataflow\n <\/li>\n
  • \n 35.<\/span> Designing a Dataflow Pipeline for Text Preprocessing and Feature Engineering\n <\/li>\n
  • \n 36.<\/span> Storing and Querying Processed Text Data in BigQuery\n <\/li>\n
  • \n 37.<\/span> Introduction to BigQuery ML for Text Analytics and Model Training\n <\/li>\n
  • \n 38.<\/span> Data Labeling for Custom Sentiment Analysis Models: Best Practices\n <\/li>\n
  • \n 39.<\/span> Utilizing Vertex AI Data Labeling Service for High-Quality Annotations\n <\/li>\n
  • \n 40.<\/span> Exporting Labeled Datasets for Model Training on Vertex AI\n <\/li>\n
  • \n 41.<\/span> Introduction to Vertex AI: The Unified Machine Learning Platform\n <\/li>\n
  • \n 42.<\/span> Vertex AI Workbench: Managed Notebooks for Development and Experimentation\n <\/li>\n
  • \n 43.<\/span> Creating and Managing Text Datasets in Vertex AI\n <\/li>\n
  • \n 44.<\/span> Preparing Text Datasets for Custom Model Training on Vertex AI\n <\/li>\n
  • \n 45.<\/span> Introduction to Custom Model Training on Vertex AI\n <\/li>\n
  • \n 46.<\/span> Training a Logistic Regression Model for Sentiment Analysis on Vertex AI\n <\/li>\n
  • \n 47.<\/span> Model Evaluation Metrics: Precision, Recall, F1-Score, and Accuracy\n <\/li>\n
  • \n 48.<\/span> Understanding ROC Curves and AUC for Sentiment Classification Models\n <\/li>\n
  • \n 49.<\/span> Hyperparameter Tuning with Vertex AI Vizier for Optimal Performance\n <\/li>\n
  • \n 50.<\/span> Custom Training Jobs with TensorFlow on Vertex AI for NLP\n <\/li>\n
  • \n 51.<\/span> Custom Training Jobs with PyTorch on Vertex AI for NLP\n <\/li>\n
  • \n 52.<\/span> Introduction to Deep Learning Architectures for Sentiment Analysis\n <\/li>\n
  • \n 53.<\/span> Recurrent Neural Networks (RNNs) for Sequence Modeling in Text\n <\/li>\n
  • \n 54.<\/span> Long Short-Term Memory (LSTMs) Networks for Capturing Long-Range Dependencies\n <\/li>\n
  • \n 55.<\/span> Gated Recurrent Units (GRUs) for Efficient Sequence Processing\n <\/li>\n
  • \n 56.<\/span> Convolutional Neural Networks (CNNs) for Text Classification\n <\/li>\n
  • \n 57.<\/span> Understanding Attention Mechanisms in NLP Models\n <\/li>\n
  • \n 58.<\/span> The Transformers Architecture: Foundation of Modern NLP\n <\/li>\n
  • \n 59.<\/span> Leveraging Pre-trained BERT Models for Domain-Specific Sentiment Analysis\n <\/li>\n
  • \n 60.<\/span> Fine-tuning BERT on Custom Sentiment Datasets with Vertex AI\n <\/li>\n
  • \n 61.<\/span> Other Transformer Models: RoBERTa, XLNet, and ELECTRA\n <\/li>\n
  • \n 62.<\/span> Advanced Transfer Learning Strategies for High-Accuracy Sentiment Models\n <\/li>\n
  • \n 63.<\/span> Aspect-Based Sentiment Analysis: Pinpointing Specific Opinions\n <\/li>\n
  • \n 64.<\/span> Implementing Aspect-Based Sentiment Models on Vertex AI\n <\/li>\n
  • \n 65.<\/span> Challenges and Solutions for Multilingual Sentiment Analysis\n <\/li>\n
  • \n 66.<\/span> Building Robust Multilingual Sentiment Models on GCP\n <\/li>\n
  • \n 67.<\/span> Handling Negation, Sarcasm, and Irony in Sentiment Analysis Systems\n <\/li>\n
  • \n 68.<\/span> Domain-Specific Sentiment Analysis: Custom Lexicons and Knowledge Bases\n <\/li>\n
  • \n 69.<\/span> Introduction to MLOps: Principles and Practices for Production ML\n <\/li>\n
  • \n 70.<\/span> Model Versioning and Lineage Tracking with Vertex AI ML Metadata\n <\/li>\n
  • \n 71.<\/span> CI\/CD for Machine Learning Models with Cloud Build and Vertex AI\n <\/li>\n
  • \n 72.<\/span> Deploying Custom Sentiment Models to Vertex AI Endpoints\n <\/li>\n
  • \n 73.<\/span> Batch Prediction for Offline Sentiment Analysis with Vertex AI\n <\/li>\n
  • \n 74.<\/span> Online Prediction for Real-time Sentiment Analysis with Vertex AI Endpoints\n <\/li>\n
  • \n 75.<\/span> Optimizing Model Inference: Quantization, Pruning, and Model Compression\n <\/li>\n
  • \n 76.<\/span> Leveraging TPUs and GPUs for Accelerated Model Training and Inference\n <\/li>\n
  • \n 77.<\/span> Designing Scalable Architectures for High-Throughput Sentiment Analysis\n <\/li>\n
  • \n 78.<\/span> Real-time Sentiment Analysis at Scale with Cloud Run and Pub\/Sub\n <\/li>\n
  • \n 79.<\/span> Autoscaling Strategies for Vertex AI Endpoints and Compute Resources\n <\/li>\n
  • \n 80.<\/span> Monitoring Model Performance, Data Drift, and Concept Drift on Vertex AI\n <\/li>\n
  • \n 81.<\/span> Detecting and Mitigating Model Bias in Sentiment Analysis Systems\n <\/li>\n
  • \n 82.<\/span> Introduction to Explainable AI (XAI) for NLP Models\n <\/li>\n
  • \n 83.<\/span> LIME and SHAP for Interpreting Sentiment Model Predictions\n <\/li>\n
  • \n 84.<\/span> Ethical Considerations and Responsible AI in NLP and Sentiment Analysis\n <\/li>\n
  • \n 85.<\/span> Data Security and Privacy Best Practices for Text Data on GCP\n <\/li>\n
  • \n 86.<\/span> Cost Optimization Strategies for GCP NLP and ML Workloads\n <\/li>\n
  • \n 87.<\/span> Troubleshooting Common Issues in GCP NLP Application Development\n <\/li>\n
  • \n 88.<\/span> Advanced Sentiment Analysis with BigQuery ML and Custom Models\n <\/li>\n
  • \n 89.<\/span> Integrating BigQuery ML with Custom Vertex AI Models for Hybrid Approaches\n <\/li>\n
  • \n 90.<\/span> Serverless Sentiment Analysis with Cloud Functions for Event-Driven Architectures\n <\/li>\n
  • \n 91.<\/span> Building a Web Application for Sentiment Analysis with App Engine or Cloud Run\n <\/li>\n
  • \n 92.<\/span> Using Data Studio for Visualizing Sentiment Trends and Insights\n <\/li>\n
  • \n 93.<\/span> Dashboarding Sentiment Analysis Results with Looker Studio\n <\/li>\n
  • \n 94.<\/span> Case Study: Social Media Sentiment Monitoring at Scale\n <\/li>\n
  • \n 95.<\/span> Case Study: Customer Feedback and Review Analysis for E-commerce\n <\/li>\n
  • \n 96.<\/span> Case Study: Market Research and Brand Reputation Management\n <\/li>\n
  • \n 97.<\/span> Best Practices for Developing Production-Ready NLP Applications on GCP\n <\/li>\n
  • \n 98.<\/span> MLOps Best Practices for Maintaining High-Accuracy Sentiment Models\n <\/li>\n
  • \n 99.<\/span> Future Trends in NLP, Large Language Models, and Sentiment Analysis\n <\/li>\n
  • \n 100.<\/span> Advanced Topics: Federated Learning for Privacy-Preserving Sentiment Analysis\n <\/li>\n<\/ul>\n<\/div>\n

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\u067e\u06cc\u0686\u06cc\u062f\u0647 \u0648 \u0645\u0642\u06cc\u0627\u0633\u200c\u067e\u0630\u06cc\u0631 \u0628\u0631\u0627\u06cc <strong>\u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a (Sentiment Analysis)<\/strong> \u0631\u0648\u06cc \u067e\u0644\u062a\u0641\u0631\u0645 \u06af\u0648\u06af\u0644 \u06a9\u0644\u0627\u062f \u0647\u0645\u0631\u0627\u0647\u06cc \u0645\u06cc\u200c\u06a9\u0646\u062f. \u0645\u0627 \u0641\u0631\u0627\u062a\u0631 \u0627\u0632 \u062a\u0626\u0648\u0631\u06cc\u200c\u0647\u0627\u06cc \u0635\u0631\u0641 \u0631\u0641\u062a\u0647 \u0648 \u0628\u0647 \u0634\u0645\u0627 \u0646\u0634\u0627\u0646 \u0645\u06cc\u200c\u062f\u0647\u06cc\u0645 \u0686\u06af\u0648\u0646\u0647 \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0633\u0631\u0648\u06cc\u0633\u200c\u0647\u0627\u06cc \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 GCP \u0645\u0627\u0646\u0646\u062f Vertex AI\u060c Natural Language API \u0648 BigQuery\u060c \u0633\u06cc\u0633\u062a\u0645\u200c\u0647\u0627\u06cc\u06cc \u0628\u0633\u0627\u0632\u06cc\u062f \u06a9\u0647 \u0642\u0627\u062f\u0631 \u0628\u0647 \u062a\u062d\u0644\u06cc\u0644 \u0645\u06cc\u0644\u06cc\u0648\u0646\u200c\u0647\u0627 \u0646\u0638\u0631 \u062f\u0631 \u0644\u062d\u0638\u0647\u060c \u0628\u0627 \u062f\u0642\u062a\u06cc \u062e\u06cc\u0631\u0647\u200c\u06a9\u0646\u0646\u062f\u0647 \u0647\u0633\u062a\u0646\u062f. \u0627\u06af\u0631 \u0622\u0645\u0627\u062f\u0647\u200c\u0627\u06cc\u062f \u062a\u0627 \u0645\u0647\u0627\u0631\u062a\u200c\u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0647 \u0633\u0637\u062d \u0628\u0627\u0644\u0627\u062a\u0631\u06cc \u0627\u0631\u062a\u0642\u0627 \u062f\u0647\u06cc\u062f \u0648 \u0628\u0647 \u06cc\u06a9 \u0645\u062a\u062e\u0635\u0635 \u0645\u0648\u0631\u062f \u062a\u0642\u0627\u0636\u0627 \u062f\u0631 \u062d\u0648\u0632\u0647 \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0648 \u0631\u0627\u06cc\u0627\u0646\u0634 \u0627\u0628\u0631\u06cc \u062a\u0628\u062f\u06cc\u0644 \u0634\u0648\u06cc\u062f\u060c \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0628\u0631\u0627\u06cc \u0634\u0645\u0627 \u0637\u0631\u0627\u062d\u06cc \u0634\u062f\u0647 \u0627\u0633\u062a.<\/p>\n<h2>\u062f\u0631\u0628\u0627\u0631\u0647 \u062f\u0648\u0631\u0647: \u0627\u0632 \u062a\u0626\u0648\u0631\u06cc \u062a\u0627 \u06cc\u06a9 \u0627\u067e\u0644\u06cc\u06a9\u06cc\u0634\u0646 \u0648\u0627\u0642\u0639\u06cc \u0648 \u06a9\u0627\u0631\u0622\u0645\u062f<\/h2>\n<p>\u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0641\u0642\u0637 \u0645\u062c\u0645\u0648\u0639\u0647\u200c\u0627\u06cc \u0627\u0632 \u0648\u06cc\u062f\u0626\u0648\u0647\u0627\u06cc \u062a\u0626\u0648\u0631\u06cc \u0646\u06cc\u0633\u062a\u061b \u0628\u0644\u06a9\u0647 \u06cc\u06a9 \u06a9\u0627\u0631\u06af\u0627\u0647 \u0639\u0645\u0644\u06cc \u0648 \u0641\u0634\u0631\u062f\u0647 \u0628\u0631\u0627\u06cc \u0633\u0627\u062e\u062a \u06cc\u06a9 \u0645\u062d\u0635\u0648\u0644 \u0648\u0627\u0642\u0639\u06cc \u0627\u0633\u062a. \u0645\u0627 \u0642\u062f\u0645 \u0628\u0647 \u0642\u062f\u0645 \u06cc\u06a9 \u0627\u067e\u0644\u06cc\u06a9\u06cc\u0634\u0646 \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a \u0631\u0627 \u0627\u0632 \u0635\u0641\u0631 \u0637\u0631\u0627\u062d\u06cc\u060c \u062a\u0648\u0633\u0639\u0647 \u0648 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0645\u06cc\u200c\u06a9\u0646\u06cc\u0645. \u0634\u0645\u0627 \u06cc\u0627\u062f \u0645\u06cc\u200c\u06af\u06cc\u0631\u06cc\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u062a\u0646\u06cc \u0631\u0627 \u062c\u0645\u0639\u200c\u0622\u0648\u0631\u06cc \u0648 \u0622\u0645\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u06a9\u0646\u06cc\u062f\u060c \u0627\u0632 API\u0647\u0627\u06cc \u0622\u0645\u0627\u062f\u0647 \u06af\u0648\u06af\u0644 \u0628\u0631\u0627\u06cc \u062a\u062d\u0644\u06cc\u0644\u200c\u0647\u0627\u06cc \u0633\u0631\u06cc\u0639 \u0628\u0647\u0631\u0647 \u0628\u0628\u0631\u06cc\u062f\u060c \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u062e\u0648\u062f \u0631\u0627 \u0628\u0627 \u062f\u0642\u062a \u0628\u0627\u0644\u0627 \u0622\u0645\u0648\u0632\u0634 \u062f\u0647\u06cc\u062f \u0648 \u062f\u0631 \u0646\u0647\u0627\u06cc\u062a\u060c \u06a9\u0644 \u0633\u06cc\u0633\u062a\u0645 \u0631\u0627 \u0628\u0647 \u0635\u0648\u0631\u062a \u06cc\u06a9 \u0633\u0631\u0648\u06cc\u0633 \u067e\u0627\u06cc\u062f\u0627\u0631 \u0648 \u0645\u0642\u06cc\u0627\u0633\u200c\u067e\u0630\u06cc\u0631 \u0631\u0648\u06cc \u0632\u06cc\u0631\u0633\u0627\u062e\u062a \u06af\u0648\u06af\u0644 \u06a9\u0644\u0627\u062f \u0645\u0633\u062a\u0642\u0631 \u06a9\u0646\u06cc\u062f. \u062a\u0645\u0631\u06a9\u0632 \u0627\u0635\u0644\u06cc \u062f\u0648\u0631\u0647 \u0628\u0631 \u0631\u0648\u06cc \u0633\u0647 \u0627\u0635\u0644 \u06a9\u0644\u06cc\u062f\u06cc \u0627\u0633\u062a: <strong>\u0645\u0642\u06cc\u0627\u0633\u200c\u067e\u0630\u06cc\u0631\u06cc (Scale)<\/strong> \u0628\u0631\u0627\u06cc \u0645\u062f\u06cc\u0631\u06cc\u062a \u062d\u062c\u0645 \u0628\u0627\u0644\u0627\u06cc \u062f\u0627\u062f\u0647\u060c <strong>\u062f\u0642\u062a \u0628\u0627\u0644\u0627 (High Accuracy)<\/strong> \u062f\u0631 \u062a\u062d\u0644\u06cc\u0644\u200c\u0647\u0627 \u0648 \u062a\u0648\u0627\u0646\u0627\u06cc\u06cc \u0645\u062f\u06cc\u0631\u06cc\u062a <strong>\u067e\u06cc\u0686\u06cc\u062f\u06af\u06cc (Complexity)<\/strong> \u062f\u0631 \u0633\u0646\u0627\u0631\u06cc\u0648\u0647\u0627\u06cc \u062f\u0646\u06cc\u0627\u06cc \u0648\u0627\u0642\u0639\u06cc.<\/p>\n<h2>\u0645\u0648\u0636\u0648\u0639\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc \u062f\u0648\u0631\u0647<\/h2>\n<ul>\n<li>\u0645\u0628\u0627\u0646\u06cc \u0648 \u0645\u0639\u0645\u0627\u0631\u06cc Google Cloud Platform \u0628\u0631\u0627\u06cc \u0645\u062a\u062e\u0635\u0635\u0627\u0646 \u062f\u0627\u062f\u0647<\/li>\n<li>\u0645\u0641\u0627\u0647\u06cc\u0645 \u0628\u0646\u06cc\u0627\u062f\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc (NLP) \u0648 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646<\/li>\n<li>\u06a9\u0627\u0631 \u0628\u0627 \u0633\u0631\u0648\u06cc\u0633 \u0642\u062f\u0631\u062a\u0645\u0646\u062f Google Cloud Natural Language API<\/li>\n<li>\u0637\u0631\u0627\u062d\u06cc \u0648 \u0633\u0627\u062e\u062a Pipeline\u0647\u0627\u06cc \u062f\u0627\u062f\u0647 \u0628\u0627 Dataflow \u0648 Pub\/Sub<\/li>\n<li>\u0630\u062e\u06cc\u0631\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u062d\u062c\u06cc\u0645 \u0628\u0627 Google BigQuery<\/li>\n<li>\u0622\u0645\u0648\u0632\u0634\u060c \u0627\u0631\u0632\u06cc\u0627\u0628\u06cc \u0648 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc NLP \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0627 Vertex AI<\/li>\n<li>\u0627\u0633\u062a\u0642\u0631\u0627\u0631 (Deployment) \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 \u0628\u0647 \u0639\u0646\u0648\u0627\u0646 \u06cc\u06a9 API \u0628\u0627 Cloud Functions \u0648 Cloud Run<\/li>\n<li>\u0627\u0635\u0648\u0644 MLOps: \u0645\u0627\u0646\u06cc\u062a\u0648\u0631\u06cc\u0646\u06af\u060c \u0645\u062f\u06cc\u0631\u06cc\u062a \u0646\u0633\u062e\u0647 \u0648 \u0627\u062a\u0648\u0645\u0627\u0633\u06cc\u0648\u0646 \u0645\u062f\u0644\u200c\u0647\u0627 \u062f\u0631 \u0645\u062d\u06cc\u0637 \u0639\u0645\u0644\u06cc\u0627\u062a\u06cc<\/li>\n<li>\u0645\u0639\u0645\u0627\u0631\u06cc \u0633\u06cc\u0633\u062a\u0645\u200c\u0647\u0627\u06cc \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a \u0628\u0631\u0627\u06cc \u06a9\u0627\u0631\u0628\u0631\u062f\u0647\u0627\u06cc \u0628\u0644\u0627\u062f\u0631\u0646\u06af (Real-time)<\/li>\n<li>\u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc \u0647\u0632\u06cc\u0646\u0647\u200c\u0647\u0627 \u0648 \u0639\u0645\u0644\u06a9\u0631\u062f \u062f\u0631 \u067e\u0644\u062a\u0641\u0631\u0645 GCP<\/li>\n<\/ul>\n<h2>\u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0628\u0631\u0627\u06cc \u0686\u0647 \u06a9\u0633\u0627\u0646\u06cc \u0645\u0646\u0627\u0633\u0628 \u0627\u0633\u062a\u061f<\/h2>\n<p>\u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0628\u0631\u0627\u06cc \u0637\u06cc\u0641 \u06af\u0633\u062a\u0631\u062f\u0647\u200c\u0627\u06cc \u0627\u0632 \u0645\u062a\u062e\u0635\u0635\u0627\u0646 \u0641\u0646\u0627\u0648\u0631\u06cc \u06a9\u0647 \u0628\u0647 \u062f\u0646\u0628\u0627\u0644 \u0648\u0631\u0648\u062f \u06cc\u0627 \u062a\u0639\u0645\u06cc\u0642 \u062f\u0627\u0646\u0634 \u062e\u0648\u062f \u062f\u0631 \u062d\u0648\u0632\u0647 \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0648 \u06a9\u0644\u0627\u062f \u0647\u0633\u062a\u0646\u062f\u060c \u0627\u06cc\u062f\u0647\u200c\u0622\u0644 \u0627\u0633\u062a:<\/p>\n<ul>\n<li><strong>\u062a\u0648\u0633\u0639\u0647\u200c\u062f\u0647\u0646\u062f\u06af\u0627\u0646 \u0646\u0631\u0645\u200c\u0627\u0641\u0632\u0627\u0631 (Software Developers):<\/strong> \u06a9\u0647 \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u0646\u062f \u0642\u0627\u0628\u0644\u06cc\u062a\u200c\u0647\u0627\u06cc \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0631\u0627 \u0628\u0647 \u0627\u067e\u0644\u06cc\u06a9\u06cc\u0634\u0646\u200c\u0647\u0627\u06cc \u062e\u0648\u062f \u0627\u0636\u0627\u0641\u0647 \u06a9\u0646\u0646\u062f.<\/li>\n<li><strong>\u062f\u0627\u0646\u0634\u0645\u0646\u062f\u0627\u0646 \u062f\u0627\u062f\u0647 (Data Scientists):<\/strong> \u06a9\u0647 \u0642\u0635\u062f \u062f\u0627\u0631\u0646\u062f \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u062e\u0648\u062f \u0631\u0627 \u0631\u0648\u06cc \u06cc\u06a9 \u0632\u06cc\u0631\u0633\u0627\u062e\u062a \u0627\u0628\u0631\u06cc \u0642\u062f\u0631\u062a\u0645\u0646\u062f \u0648 \u0645\u0642\u06cc\u0627\u0633\u200c\u067e\u0630\u06cc\u0631 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u06a9\u0646\u0646\u062f.<\/li>\n<li><strong>\u0645\u0647\u0646\u062f\u0633\u0627\u0646 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 (Machine Learning Engineers):<\/strong> \u06a9\u0647 \u0628\u0647 \u062f\u0646\u0628\u0627\u0644 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0628\u0647\u062a\u0631\u06cc\u0646 \u0631\u0648\u0634\u200c\u0647\u0627 \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0648 \u0645\u062f\u06cc\u0631\u06cc\u062a \u0645\u062f\u0644\u200c\u0647\u0627 (MLOps) \u062f\u0631 GCP \u0647\u0633\u062a\u0646\u062f.<\/li>\n<li><strong>\u0645\u0647\u0646\u062f\u0633\u0627\u0646 \u062f\u0627\u062f\u0647 (Data Engineers):<\/strong> \u06a9\u0647 \u0645\u06cc\u200c\u062e\u0648\u0627\u0647\u0646\u062f Pipeline\u0647\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u062a\u0646\u06cc \u0631\u0627 \u062f\u0631 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0632\u0631\u06af \u0637\u0631\u0627\u062d\u06cc \u06a9\u0646\u0646\u062f.<\/li>\n<li><strong>\u0645\u0639\u0645\u0627\u0631\u0627\u0646 \u06a9\u0644\u0627\u062f (Cloud Architects):<\/strong> \u06a9\u0647 \u0646\u06cc\u0627\u0632 \u0628\u0647 \u062f\u0631\u06a9 \u0639\u0645\u06cc\u0642 \u0627\u0632 \u0633\u0631\u0648\u06cc\u0633\u200c\u0647\u0627\u06cc AI\/ML \u06af\u0648\u06af\u0644 \u0628\u0631\u0627\u06cc \u0637\u0631\u0627\u062d\u06cc \u0631\u0627\u0647\u200c\u062d\u0644\u200c\u0647\u0627\u06cc \u0628\u0647\u06cc\u0646\u0647 \u062f\u0627\u0631\u0646\u062f.<\/li>\n<li><strong>\u062f\u0627\u0646\u0634\u062c\u0648\u06cc\u0627\u0646 \u0648 \u0641\u0627\u0631\u063a\u200c\u0627\u0644\u062a\u062d\u0635\u06cc\u0644\u0627\u0646 \u0631\u0634\u062a\u0647\u200c\u0647\u0627\u06cc \u06a9\u0627\u0645\u067e\u06cc\u0648\u062a\u0631 \u0648 IT:<\/strong> \u06a9\u0647 \u0628\u0647 \u062f\u0646\u0628\u0627\u0644 \u06a9\u0633\u0628 \u06cc\u06a9 \u0645\u0647\u0627\u0631\u062a \u062a\u062e\u0635\u0635\u06cc\u060c \u067e\u0631\u062f\u0631\u0622\u0645\u062f \u0648 \u0622\u06cc\u0646\u062f\u0647\u200c\u062f\u0627\u0631 \u0647\u0633\u062a\u0646\u062f.<\/li>\n<\/ul>\n<h2>\u0686\u0631\u0627 \u0628\u0627\u06cc\u062f \u062f\u0631 \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0634\u0631\u06a9\u062a \u06a9\u0646\u06cc\u062f\u061f<\/h2>\n<h3>\u0645\u062a\u062e\u0635\u0635 \u0645\u0648\u0631\u062f \u062a\u0642\u0627\u0636\u0627\u06cc \u0628\u0627\u0632\u0627\u0631 \u0634\u0648\u06cc\u062f<\/h3>\n<p>\u062a\u0631\u06a9\u06cc\u0628 \u0645\u0647\u0627\u0631\u062a \u062f\u0631 <strong>Google Cloud<\/strong> \u0648 <strong>\u067e\u0631\u062f\u0627\u0632\u0634 \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc<\/strong> \u06cc\u06a9\u06cc \u0627\u0632 \u06a9\u0645\u06cc\u0627\u0628\u200c\u062a\u0631\u06cc\u0646 \u0648 \u067e\u0631\u062f\u0631\u0622\u0645\u062f\u062a\u0631\u06cc\u0646 \u062a\u062e\u0635\u0635\u200c\u0647\u0627 \u062f\u0631 \u062f\u0646\u06cc\u0627\u06cc \u062a\u06a9\u0646\u0648\u0644\u0648\u0698\u06cc \u0627\u0645\u0631\u0648\u0632 \u0627\u0633\u062a. \u0628\u0627 \u06af\u0630\u0631\u0627\u0646\u062f\u0646 \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647\u060c \u0634\u0645\u0627 \u0628\u0647 \u0645\u062a\u062e\u0635\u0635\u06cc \u062a\u0628\u062f\u06cc\u0644 \u0645\u06cc\u200c\u0634\u0648\u06cc\u062f \u06a9\u0647 \u0634\u0631\u06a9\u062a\u200c\u0647\u0627\u06cc \u0628\u0632\u0631\u06af \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u062e\u062f\u0627\u0645 \u0627\u0648 \u0631\u0642\u0627\u0628\u062a \u0645\u06cc\u200c\u06a9\u0646\u0646\u062f.<\/p>\n<h3>\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u06a9\u0627\u0645\u0644\u0627\u064b \u0639\u0645\u0644\u06cc \u0648 \u067e\u0631\u0648\u0698\u0647-\u0645\u062d\u0648\u0631<\/h3>\n<p>\u0645\u0627 \u0628\u0647 \u0634\u0645\u0627 \u0645\u0627\u0647\u06cc\u06af\u06cc\u0631\u06cc \u06cc\u0627\u062f \u0645\u06cc\u200c\u062f\u0647\u06cc\u0645! \u0628\u0647 \u062c\u0627\u06cc \u062d\u0641\u0638 \u06a9\u0631\u062f\u0646 \u0645\u0641\u0627\u0647\u06cc\u0645\u060c \u0634\u0645\u0627 \u06cc\u06a9 \u067e\u0631\u0648\u0698\u0647 \u0648\u0627\u0642\u0639\u06cc \u0648 \u06a9\u0627\u0645\u0644 \u0631\u0627 \u0627\u0632 \u0627\u0628\u062a\u062f\u0627 \u062a\u0627 \u0627\u0646\u062a\u0647\u0627 \u067e\u06cc\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0645\u06cc\u200c\u06a9\u0646\u06cc\u062f. \u0627\u06cc\u0646 \u062a\u062c\u0631\u0628\u0647 \u0639\u0645\u0644\u06cc\u060c \u0627\u0639\u062a\u0645\u0627\u062f \u0628\u0647 \u0646\u0641\u0633 \u0644\u0627\u0632\u0645 \u0628\u0631\u0627\u06cc \u062d\u0644 \u0686\u0627\u0644\u0634\u200c\u0647\u0627\u06cc \u0645\u0634\u0627\u0628\u0647 \u062f\u0631 \u0645\u062d\u06cc\u0637 \u06a9\u0627\u0631 \u0648\u0627\u0642\u0639\u06cc \u0631\u0627 \u0628\u0647 \u0634\u0645\u0627 \u0645\u06cc\u200c\u062f\u0647\u062f.<\/p>\n<h3>\u062a\u0633\u0644\u0637 \u0628\u0631 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u067e\u06cc\u0634\u0631\u0641\u062a\u0647 \u06af\u0648\u06af\u0644<\/h3>\n<p>\u0634\u0645\u0627 \u0646\u0647 \u062a\u0646\u0647\u0627 \u0628\u0627 \u06cc\u06a9 \u06cc\u0627 \u062f\u0648 \u0633\u0631\u0648\u06cc\u0633\u060c \u0628\u0644\u06a9\u0647 \u0628\u0627 \u0627\u06a9\u0648\u0633\u06cc\u0633\u062a\u0645 \u06a9\u0627\u0645\u0644 \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0648 \u062f\u0627\u062f\u0647 \u06af\u0648\u06af\u0644 \u0622\u0634\u0646\u0627 \u0645\u06cc\u200c\u0634\u0648\u06cc\u062f. \u0627\u06cc\u0646 \u062a\u0633\u0644\u0637 \u0628\u0647 \u0634\u0645\u0627 \u0627\u0645\u06a9\u0627\u0646 \u0645\u06cc\u200c\u062f\u0647\u062f \u062a\u0627 \u0628\u0631\u0627\u06cc \u0647\u0631 \u0686\u0627\u0644\u0634\u06cc\u060c \u0628\u0647\u062a\u0631\u06cc\u0646 \u0648 \u0628\u0647\u06cc\u0646\u0647\u200c\u062a\u0631\u06cc\u0646 \u0631\u0627\u0647\u200c\u062d\u0644 \u0631\u0627 \u0637\u0631\u0627\u062d\u06cc \u06a9\u0646\u06cc\u062f.<\/p>\n<h3>\u0633\u0627\u062e\u062a \u0633\u06cc\u0633\u062a\u0645\u200c\u0647\u0627\u06cc \u0645\u0642\u06cc\u0627\u0633\u200c\u067e\u0630\u06cc\u0631 \u0631\u0627 \u0628\u06cc\u0627\u0645\u0648\u0632\u06cc\u062f<\/h3>\n<p>\u0628\u0633\u06cc\u0627\u0631\u06cc \u0627\u0632 \u062f\u0648\u0631\u0647\u200c\u0647\u0627 \u0628\u0647 \u0634\u0645\u0627 \u0622\u0645\u0648\u0632\u0634 \u0633\u0627\u062e\u062a \u0645\u062f\u0644 \u0631\u0627 \u0645\u06cc\u200c\u062f\u0647\u0646\u062f\u060c \u0627\u0645\u0627 \u062a\u0639\u062f\u0627\u062f \u06a9\u0645\u06cc \u0628\u0647 \u0634\u0645\u0627 \u0645\u06cc\u200c\u0622\u0645\u0648\u0632\u0646\u062f \u06a9\u0647 \u0686\u06af\u0648\u0646\u0647 \u0633\u06cc\u0633\u062a\u0645\u06cc \u0628\u0633\u0627\u0632\u06cc\u062f \u06a9\u0647 \u0628\u062a\u0648\u0627\u0646\u062f \u0628\u0647 \u0645\u06cc\u0644\u06cc\u0648\u0646\u200c\u0647\u0627 \u06a9\u0627\u0631\u0628\u0631 \u0628\u0647 \u0635\u0648\u0631\u062a \u0647\u0645\u0632\u0645\u0627\u0646 \u0633\u0631\u0648\u06cc\u0633\u200c\u062f\u0647\u06cc \u06a9\u0646\u062f. \u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0627\u06cc\u0646 \u062e\u0644\u0627\u0621 \u0631\u0627 \u067e\u0631 \u0645\u06cc\u200c\u06a9\u0646\u062f.<\/p>\n<h3>\u0622\u06cc\u0646\u062f\u0647 \u0634\u063a\u0644\u06cc \u062e\u0648\u062f \u0631\u0627 \u062a\u0636\u0645\u06cc\u0646 \u06a9\u0646\u06cc\u062f<\/h3>\n<p>\u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u0648 \u0631\u0627\u06cc\u0627\u0646\u0634 \u0627\u0628\u0631\u06cc\u060c \u062a\u06a9\u0646\u0648\u0644\u0648\u0698\u06cc\u200c\u0647\u0627\u06cc \u0622\u06cc\u0646\u062f\u0647 \u0646\u06cc\u0633\u062a\u0646\u062f\u061b \u0628\u0644\u06a9\u0647 \u062d\u0627\u0644 \u062d\u0627\u0636\u0631 \u062f\u0646\u06cc\u0627\u06cc \u0641\u0646\u0627\u0648\u0631\u06cc \u0647\u0633\u062a\u0646\u062f. \u0633\u0631\u0645\u0627\u06cc\u0647\u200c\u06af\u0630\u0627\u0631\u06cc \u0631\u0648\u06cc \u0627\u06cc\u0646 \u062f\u0627\u0646\u0634\u060c \u0628\u0647\u062a\u0631\u06cc\u0646 \u0633\u0631\u0645\u0627\u06cc\u0647\u200c\u06af\u0630\u0627\u0631\u06cc \u0631\u0648\u06cc \u0622\u06cc\u0646\u062f\u0647 \u062d\u0631\u0641\u0647\u200c\u0627\u06cc \u0634\u0645\u0627\u0633\u062a.<\/p>\n<h2>\u0646\u06af\u0627\u0647\u06cc \u0628\u0647 \u06af\u0646\u062c\u06cc\u0646\u0647 \u06f1\u06f0\u06f0 \u0633\u0631\u0641\u0635\u0644 \u062c\u0627\u0645\u0639 \u062f\u0648\u0631\u0647<\/h2>\n<p>\u0627\u06cc\u0646 \u062f\u0648\u0631\u0647 \u0628\u0627 \u0628\u06cc\u0634 \u0627\u0632 <strong>\u06f1\u06f0\u06f0 \u0633\u0631\u0641\u0635\u0644 \u062f\u0642\u06cc\u0642 \u0648 \u0637\u0628\u0642\u0647\u200c\u0628\u0646\u062f\u06cc \u0634\u062f\u0647<\/strong>\u060c \u0639\u0645\u06cc\u0642\u200c\u062a\u0631\u06cc\u0646 \u0648 \u062c\u0627\u0645\u0639\u200c\u062a\u0631\u06cc\u0646 \u0645\u062d\u062a\u0648\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u062f\u0631 \u0627\u06cc\u0646 \u062d\u0648\u0632\u0647 \u0631\u0627 \u0628\u0647 \u0632\u0628\u0627\u0646 \u0641\u0627\u0631\u0633\u06cc \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc\u200c\u062f\u0647\u062f. \u0645\u0627 \u0647\u06cc\u0686 \u0646\u06a9\u062a\u0647\u200c\u0627\u06cc \u0631\u0627 \u0646\u0627\u06af\u0641\u062a\u0647 \u0628\u0627\u0642\u06cc \u0646\u06af\u0630\u0627\u0634\u062a\u0647\u200c\u0627\u06cc\u0645. \u0633\u0631\u0641\u0635\u0644\u200c\u0647\u0627 \u0628\u0647 \u06af\u0648\u0646\u0647\u200c\u0627\u06cc \u0637\u0631\u0627\u062d\u06cc \u0634\u062f\u0647\u200c\u0627\u0646\u062f \u06a9\u0647 \u0634\u0645\u0627 \u0631\u0627 \u0627\u0632 \u06cc\u06a9 \u0641\u0631\u062f \u0645\u0628\u062a\u062f\u06cc \u062f\u0631 GCP \u0628\u0647 \u06cc\u06a9 \u0645\u062a\u062e\u0635\u0635 \u062d\u0631\u0641\u0647\u200c\u0627\u06cc \u062f\u0631 \u0632\u0645\u06cc\u0646\u0647 \u0633\u0627\u062e\u062a \u0627\u067e\u0644\u06cc\u06a9\u06cc\u0634\u0646\u200c\u0647\u0627\u06cc NLP \u062a\u0628\u062f\u06cc\u0644 \u06a9\u0646\u0646\u062f. \u0628\u0631\u062e\u06cc \u0627\u0632 \u0645\u0627\u0698\u0648\u0644\u200c\u0647\u0627\u06cc \u0627\u0635\u0644\u06cc \u062f\u0648\u0631\u0647 \u0639\u0628\u0627\u0631\u062a\u0646\u062f \u0627\u0632:<\/p>\n<ul>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f1: \u0645\u0628\u0627\u0646\u06cc Google Cloud \u0648 \u0622\u0645\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u0645\u062d\u06cc\u0637 \u06a9\u0627\u0631\u06cc<\/strong> (\u0634\u0627\u0645\u0644 \u0622\u0634\u0646\u0627\u06cc\u06cc \u0628\u0627 \u06a9\u0646\u0633\u0648\u0644\u060c IAM\u060c Billing \u0648 \u0627\u0628\u0632\u0627\u0631\u0647\u0627\u06cc \u062e\u0637 \u0641\u0631\u0645\u0627\u0646)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f2: \u0645\u0641\u0627\u0647\u06cc\u0645 \u06a9\u0644\u06cc\u062f\u06cc NLP \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a<\/strong> (\u0627\u0632 \u062a\u0648\u06a9\u0646\u06cc\u0632\u06cc\u0634\u0646 \u062a\u0627 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0645\u0628\u062a\u0646\u06cc \u0628\u0631 \u062a\u0631\u0646\u0633\u0641\u0648\u0631\u0645\u0631)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f3: \u062a\u062d\u0644\u06cc\u0644 \u0633\u0631\u06cc\u0639 \u0628\u0627 Cloud Natural Language API<\/strong> (\u06a9\u0627\u0631\u0628\u0631\u062f\u0647\u0627\u06cc \u0639\u0645\u0644\u06cc\u060c \u062a\u062d\u0644\u06cc\u0644 \u0645\u0648\u062c\u0648\u062f\u06cc\u062a\u060c \u0646\u062d\u0648 \u0648 \u0627\u062d\u0633\u0627\u0633\u0627\u062a)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f4: \u0645\u0639\u0645\u0627\u0631\u06cc Pipeline \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u062a\u0646\u06cc<\/strong> (\u0637\u0631\u0627\u062d\u06cc \u0628\u0627 Pub\/Sub, Cloud Functions \u0648 Dataflow)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f5: \u0630\u062e\u06cc\u0631\u0647\u200c\u0633\u0627\u0632\u06cc \u0648 \u067e\u0631\u062f\u0627\u0632\u0634 \u06a9\u0644\u0627\u0646-\u062f\u0627\u062f\u0647 \u0628\u0627 BigQuery<\/strong> (\u0646\u0648\u0634\u062a\u0646 \u06a9\u0648\u0626\u0631\u06cc\u200c\u0647\u0627\u06cc \u0628\u0647\u06cc\u0646\u0647 \u0628\u0631\u0627\u06cc \u062f\u0627\u062f\u0647\u200c\u0647\u0627\u06cc \u0645\u062a\u0646\u06cc)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f6: \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0627 Vertex AI – \u0628\u062e\u0634 \u0627\u0648\u0644<\/strong> (\u0622\u0645\u0627\u062f\u0647\u200c\u0633\u0627\u0632\u06cc \u062f\u06cc\u062a\u0627\u0633\u062a\u060c AutoML \u0648 \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u067e\u06cc\u0634\u200c\u0633\u0627\u062e\u062a\u0647)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f7: \u0622\u0645\u0648\u0632\u0634 \u0645\u062f\u0644 \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0627 Vertex AI – \u0628\u062e\u0634 \u062f\u0648\u0645<\/strong> (\u06a9\u062f\u0646\u0648\u06cc\u0633\u06cc \u0645\u062f\u0644\u200c\u0647\u0627\u06cc \u0633\u0641\u0627\u0631\u0634\u06cc \u0628\u0627 TensorFlow\/PyTorch \u0631\u0648\u06cc \u067e\u0644\u062a\u0641\u0631\u0645)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f8: \u0627\u0633\u062a\u0642\u0631\u0627\u0631 \u0648 \u0633\u0631\u0648\u06cc\u0633\u200c\u062f\u0647\u06cc \u0645\u062f\u0644 (Model Serving)<\/strong> (\u0645\u0642\u0627\u06cc\u0633\u0647 Cloud Run, Cloud Functions \u0648 GKE \u0628\u0631\u0627\u06cc \u0627\u0633\u062a\u0642\u0631\u0627\u0631)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f9: \u0627\u0635\u0648\u0644 MLOps \u062f\u0631 \u0639\u0645\u0644<\/strong> (\u0633\u0627\u062e\u062a CI\/CD Pipeline \u0628\u0631\u0627\u06cc \u0645\u062f\u0644\u200c\u0647\u0627 \u0628\u0627 Cloud Build \u0648 Vertex AI Pipelines)<\/li>\n<li><strong>\u0645\u0627\u0698\u0648\u0644 \u06f1\u06f0: \u067e\u0631\u0648\u0698\u0647 \u0646\u0647\u0627\u06cc\u06cc \u0648 \u0628\u0647\u06cc\u0646\u0647\u200c\u0633\u0627\u0632\u06cc<\/strong> (\u062c\u0645\u0639\u200c\u0628\u0646\u062f\u06cc \u067e\u0631\u0648\u0698\u0647\u060c \u062a\u0633\u062a \u0628\u0627\u0631\u060c \u0645\u0627\u0646\u06cc\u062a\u0648\u0631\u06cc\u0646\u06af \u0648 \u0645\u062f\u06cc\u0631\u06cc\u062a \u0647\u0632\u06cc\u0646\u0647\u200c\u0647\u0627)<\/li>\n<\/ul>\n<p><strong>\u0647\u0645\u06cc\u0646 \u0627\u0645\u0631\u0648\u0632 \u0633\u0641\u0631 \u062e\u0648\u062f \u0631\u0627 \u0628\u0631\u0627\u06cc \u062a\u0628\u062f\u06cc\u0644 \u0634\u062f\u0646 \u0628\u0647 \u06cc\u06a9 \u0645\u062a\u062e\u0635\u0635 \u0647\u0648\u0634 \u0645\u0635\u0646\u0648\u0639\u06cc \u062f\u0631 \u067e\u0644\u062a\u0641\u0631\u0645 \u0627\u0628\u0631\u06cc \u06af\u0648\u06af\u0644 \u0622\u063a\u0627\u0632 \u06a9\u0646\u06cc\u062f \u0648 \u0622\u06cc\u0646\u062f\u0647 \u0634\u063a\u0644\u06cc \u062e\u0648\u062f \u0631\u0627 \u0645\u062a\u062d\u0648\u0644 \u0633\u0627\u0632\u06cc\u062f!<\/strong><\/p>\n<p><\/body><br \/>\n<\/html><\/div>\n<div\r\n style=\"border: 2px dashed #4CAF50; border-radius: 16px; padding: 20px; background: #f9fff9; font-family: 'IRANSans', sans-serif;\">\r\n <h2 style=\"color: #2E7D32; margin-top: 0;\">\ud83d\udcda \u0645\u062d\u062a\u0648\u0627\u06cc \u0627\u06cc\u0646 \u0645\u062d\u0635\u0648\u0644 \u0622\u0645\u0648\u0632\u0634\u06cc (\u067e\u06a9\u06cc\u062c \u06a9\u0627\u0645\u0644)<\/h2>\r\n <div\r\n style=\"background: #E8F5E9; border-radius: 12px; padding: 15px 20px; margin-bottom: 20px; border: 1px solid #A5D6A7;\">\r\n <h3 style=\"color: #1B5E20; margin-top: 0;\">\ud83d\udca1 \u0627\u06cc\u0646 \u0645\u062d\u0635\u0648\u0644 \u06cc\u06a9 \u0646\u0633\u062e\u0647\u0654 \u06a9\u0627\u0645\u0644 \u0648 \u062c\u0627\u0645\u0639 \u0627\u0633\u062a<\/h3>\r\n <p style=\"font-size:16px; line-height:1.8; color:#2E7D32; margin:0;\"> \u062a\u0645\u0627\u0645\u06cc \u0645\u062d\u062a\u0648\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0627\u06cc\u0646 \u06a9\u062a\u0627\u0628 \u062f\u0631 \u0642\u0627\u0644\u0628 \u06cc\u06a9\r\n \u0628\u0633\u062a\u0647\u200c\u06cc \u06a9\u0627\u0645\u0644 \u0648 \u06cc\u06a9\u067e\u0627\u0631\u0686\u0647 \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f \u0648 \u0634\u0627\u0645\u0644 \u062a\u0645\u0627\u0645 \u0646\u0633\u062e\u0647\u200c\u0647\u0627 \u0648 \u0641\u0627\u06cc\u0644\u200c\u0647\u0627\u06cc \u0645\u0648\u0631\u062f\u0646\u06cc\u0627\u0632 \u0628\u0631\u0627\u06cc \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0627\u0633\u062a. <\/p>\r\n <\/div>\r\n <h3 style=\"color: #2E7D32;\">\ud83c\udf81 \u0645\u062d\u062a\u0648\u06cc\u0627\u062a \u06a9\u0627\u0645\u0644 \u0628\u0633\u062a\u0647 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc<\/h3>\r\n\r\n\t\r\n<ul style=\"list-style-type: '\u2705 '; padding-left: 20px; font-size: 16px; line-height: 1.8;\">\r\n <li><strong>\u0648\u06cc\u062f\u06cc\u0648\u0647\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc \u0641\u0627\u0631\u0633\u06cc<\/strong> \u2014 \u0622\u0645\u0648\u0632\u0634 \u0642\u062f\u0645\u200c\u0628\u0647\u200c\u0642\u062f\u0645\u060c \u06a9\u0627\u0631\u0628\u0631\u062f\u06cc \u0648 \u0642\u0627\u0628\u0644 \u0641\u0647\u0645<\/li>\r\n <li><strong>\u067e\u0627\u062f\u06a9\u0633\u062a\u200c\u0647\u0627\u06cc \u0635\u0648\u062a\u06cc \u0641\u0627\u0631\u0633\u06cc<\/strong> \u2014 \u062a\u0648\u0636\u06cc\u062d \u0645\u0641\u0627\u0647\u06cc\u0645 \u06a9\u0644\u06cc\u062f\u06cc \u0648 \u0646\u06a9\u0627\u062a \u062a\u06a9\u0645\u06cc\u0644\u06cc<\/li>\r\n <li><strong>\u06a9\u062a\u0627\u0628 PDF \u0641\u0627\u0631\u0633\u06cc<\/strong> \u2014 \u0634\u0627\u0645\u0644 \u06a9\u0644\u06cc\u0647\u0654 \u0633\u0631\u0641\u0635\u0644\u200c\u0647\u0627 \u0648 \u0645\u062d\u062a\u0648\u0627\u06cc \u0622\u0645\u0648\u0632\u0634\u06cc<\/li>\r\n <li><strong>\u06a9\u062a\u0627\u0628 \u062e\u0644\u0627\u0635\u0647 \u0646\u06a9\u0627\u062a \u0648\u06cc\u062f\u06cc\u0648\u0647\u0627 \u0648 \u067e\u0627\u062f\u06a9\u0633\u062a\u200c\u0647\u0627 \u2013 \u0646\u0633\u062e\u0647 PDF<\/strong> \u2014 \u0645\u0646\u0627\u0633\u0628 \u0645\u0631\u0648\u0631 \u0633\u0631\u06cc\u0639 \u0648 \u062c\u0645\u0639\u200c\u0628\u0646\u062f\u06cc \u0645\u0628\u0627\u062d\u062b<\/li>\r\n <li><strong>\u06a9\u062a\u0627\u0628 \u0635\u062f\u0647\u0627 \u0646\u06a9\u062a\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062e\u0648\u062f\u0645\u0648\u0646\u06cc) \u2013 \u0646\u0633\u062e\u0647 PDF<\/strong> \u2014 \u0632\u0628\u0627\u0646 \u0633\u0627\u062f\u0647 \u0648 \u06a9\u0627\u0631\u0628\u0631\u062f\u06cc<\/li>\r\n <li><strong>\u06a9\u062a\u0627\u0628 \u0635\u062f\u0647\u0627 \u0646\u06a9\u062a\u0647 \u0631\u0633\u0645\u06cc \u0641\u0627\u0631\u0633\u06cc \u2013 \u0646\u0633\u062e\u0647 PDF<\/strong> \u2014 \u0646\u06af\u0627\u0631\u0634 \u0627\u0633\u062a\u0627\u0646\u062f\u0627\u0631\u062f\u060c \u0639\u0644\u0645\u06cc \u0648 \u0645\u0646\u0627\u0633\u0628 \u0686\u0627\u067e<\/li>\r\n\r\n <li>\r\n <strong>\u06a9\u062a\u0627\u0628 \u0635\u062f\u0647\u0627 \u067e\u0631\u0633\u0634 \u0648 \u067e\u0627\u0633\u062e \u062a\u0634\u0631\u06cc\u062d\u06cc \u2013 \u0646\u0633\u062e\u0647 PDF<\/strong><br>\r\n \u2014 \u0647\u0631 \u0633\u0624\u0627\u0644 \u0628\u0644\u0627\u0641\u0627\u0635\u0644\u0647 \u0647\u0645\u0631\u0627\u0647 \u0628\u0627 \u067e\u0627\u0633\u062e \u06a9\u0627\u0645\u0644 \u0648 \u0634\u0641\u0627\u0641 \u0627\u0631\u0627\u0626\u0647 \u0634\u062f\u0647 \u0627\u0633\u062a\u061b \u0645\u0646\u0627\u0633\u0628 \u062f\u0631\u06a9 \u0639\u0645\u06cc\u0642 \u0645\u0641\u0627\u0647\u06cc\u0645 \u0648 \u0631\u0641\u0639 \u0627\u0628\u0647\u0627\u0645.\r\n <\/li>\r\n\r\n <li>\r\n <strong>\u06a9\u062a\u0627\u0628 \u0635\u062f\u0647\u0627 \u067e\u0631\u0633\u0634 \u0648 \u067e\u0627\u0633\u062e \u0686\u0647\u0627\u0631\u06af\u0632\u06cc\u0646\u0647\u200c\u0627\u06cc \u2013 \u0646\u0633\u062e\u0647 PDF (\u0646\u0633\u062e\u0647 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0633\u0631\u06cc\u0639)<\/strong><br>\r\n \u2014 \u067e\u0627\u0633\u062e\u200c\u0647\u0627 \u0628\u0644\u0627\u0641\u0627\u0635\u0644\u0647 \u067e\u0633 \u0627\u0632 \u0633\u0624\u0627\u0644 \u0642\u0631\u0627\u0631 \u062f\u0627\u0631\u0646\u062f\u061b \u0645\u0646\u0627\u0633\u0628 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0633\u0631\u06cc\u0639 \u0648 \u062a\u062b\u0628\u06cc\u062a \u0645\u0637\u0627\u0644\u0628.\r\n <\/li>\r\n\r\n <li>\r\n <strong>\u06a9\u062a\u0627\u0628 \u0635\u062f\u0647\u0627 \u067e\u0631\u0633\u0634 \u0648 \u067e\u0627\u0633\u062e \u0686\u0647\u0627\u0631\u06af\u0632\u06cc\u0646\u0647\u200c\u0627\u06cc \u2013 \u0646\u0633\u062e\u0647 PDF (\u0646\u0633\u062e\u0647 \u062e\u0648\u062f\u0622\u0632\u0645\u0627\u06cc\u06cc \u067e\u0627\u06cc\u0627\u0646\u200c\u0628\u062e\u0634)<\/strong><br>\r\n \u2014 \u067e\u0627\u0633\u062e\u200c\u0647\u0627 \u062f\u0631 \u0627\u0646\u062a\u0647\u0627\u06cc \u0647\u0631 \u0628\u062e\u0634 \u0622\u0645\u062f\u0647\u200c\u0627\u0646\u062f\u061b \u0645\u0646\u0627\u0633\u0628 \u0622\u0632\u0645\u0648\u0646 \u0648\u0627\u0642\u0639\u06cc \u0648 \u0633\u0646\u062c\u0634 \u0645\u06cc\u0632\u0627\u0646 \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc.\r\n <\/li>\r\n\r\n <li>\r\n <strong>\u06a9\u062a\u0627\u0628 \u062a\u0645\u0631\u06cc\u0646\u200c\u0647\u0627\u06cc \u062f\u0631\u0633\u062a \/ \u0646\u0627\u062f\u0631\u0633\u062a (True \/ False) \u2013 \u0646\u0633\u062e\u0647 PDF<\/strong><br>\r\n \u2014 \u0645\u0646\u0627\u0633\u0628 \u0627\u0641\u0632\u0627\u06cc\u0634 \u062f\u0642\u062a \u0645\u0641\u0647\u0648\u0645\u06cc \u0648 \u062a\u0634\u062e\u06cc\u0635 \u0635\u062d\u06cc\u062d \u06cc\u0627 \u0646\u0627\u062f\u0631\u0633\u062a \u0628\u0648\u062f\u0646 \u06af\u0632\u0627\u0631\u0647\u200c\u0647\u0627.\r\n <\/li>\r\n\r\n <li>\r\n <strong>\u06a9\u062a\u0627\u0628 \u062a\u0645\u0631\u06cc\u0646\u200c\u0647\u0627\u06cc \u062c\u0627\u06cc \u062e\u0627\u0644\u06cc \u2013 \u0646\u0633\u062e\u0647 PDF<\/strong><br>\r\n \u2014 \u062a\u0642\u0648\u06cc\u062a \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0641\u0639\u0627\u0644 \u0648 \u062a\u0633\u0644\u0637 \u0628\u0631 \u0645\u0641\u0627\u0647\u06cc\u0645 \u0648 \u0627\u0635\u0637\u0644\u0627\u062d\u0627\u062a \u06a9\u0644\u06cc\u062f\u06cc.\r\n <\/li>\r\n<\/ul>\r\n\t\r\n\t\r\n\t\r\n\t\r\n <p style=\"color: #388E3C; font-weight: bold; font-size: 18px; margin-top: 20px;\"> \ud83c\udfaf \u0627\u06cc\u0646 \u0628\u0633\u062a\u0647 \u06cc\u06a9 \u062f\u0648\u0631\u0647\u0654 \u0622\u0645\u0648\u0632\u0634\u06cc \u06a9\u0627\u0645\u0644 \u0648\r\n \u0686\u0646\u062f\u0644\u0627\u06cc\u0647 \u0627\u0633\u062a\u061b \u0634\u0627\u0645\u0644 \u0622\u0645\u0648\u0632\u0634 \u062a\u0635\u0648\u06cc\u0631\u06cc\u060c \u0635\u0648\u062a\u06cc\u060c \u06a9\u062a\u0627\u0628\u200c\u0647\u0627\u060c \u062a\u0645\u0631\u06cc\u0646\u200c\u0647\u0627 \u0648 \u062e\u0648\u062f\u0622\u0632\u0645\u0627\u06cc\u06cc . <\/p>\r\n <hr style=\"border: none; border-top: 1px dashed #81C784; margin: 20px 0;\">\r\n <h3 style=\"color: #2E7D32;\">\u2139\ufe0f \u0646\u06a9\u0627\u062a \u0645\u0647\u0645 \u0647\u0646\u06af\u0627\u0645 \u062e\u0631\u06cc\u062f<\/h3>\r\n <ul style=\"list-style-type: '\ud83d\udd38 '; padding-left: 20px; font-size: 15px; line-height: 1.9;\">\r\n <li>\u0627\u06cc\u0646 \u0645\u062d\u0635\u0648\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a <strong>\u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc \u06a9\u0627\u0645\u0644<\/strong> \u0627\u0631\u0627\u0626\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f \u0648 \u0646\u0633\u062e\u0647\u0654 \u0686\u0627\u067e\u06cc \u0646\u062f\u0627\u0631\u062f.<\/li>\r\n <li>\u062a\u0645\u0627\u0645\u06cc \u0641\u0627\u06cc\u0644\u200c\u0647\u0627 \u0648 \u06a9\u062a\u0627\u0628\u200c\u0647\u0627 <strong>\u06a9\u0627\u0645\u0644\u0627\u064b \u0641\u0627\u0631\u0633\u06cc<\/strong> \u0647\u0633\u062a\u0646\u062f.<\/li>\r\n <li><strong>\u062a\u0648\u062c\u0647:<\/strong> \u0644\u06cc\u0646\u06a9\u200c\u0647\u0627\u06cc \u0627\u062e\u062a\u0635\u0627\u0635\u06cc \u062f\u0648\u0631\u0647 \u0637\u06cc <strong>\u06f4\u06f8 \u0633\u0627\u0639\u062a<\/strong> \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634 \u0627\u0631\u0633\u0627\u0644 \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/li>\r\n <li>\u0646\u06cc\u0627\u0632\u06cc \u0628\u0647 \u062f\u0631\u062c \u0634\u0645\u0627\u0631\u0647 \u0645\u0648\u0628\u0627\u06cc\u0644 \u0646\u06cc\u0633\u062a\u061b \u0627\u0645\u0627 \u0628\u0631\u0627\u06cc \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc \u0633\u0631\u06cc\u0639\u200c\u062a\u0631 \u062a\u0648\u0635\u06cc\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/li>\r\n <li>\u062f\u0631 \u0635\u0648\u0631\u062a \u0628\u0631\u0648\u0632 \u0645\u0634\u06a9\u0644 \u062f\u0631 \u062f\u0627\u0646\u0644\u0648\u062f \u0628\u0627 \u0634\u0645\u0627\u0631\u0647 <strong>09395106248<\/strong> \u062a\u0645\u0627\u0633 \u0628\u06af\u06cc\u0631\u06cc\u062f.<\/li>\r\n <li>\u0627\u06af\u0631 \u067e\u0631\u062f\u0627\u062e\u062a \u0627\u0646\u062c\u0627\u0645 \u0634\u062f\u0647 \u0648\u0644\u06cc \u0644\u06cc\u0646\u06a9\u200c\u0647\u0627 \u0631\u0627 \u062f\u0631\u06cc\u0627\u0641\u062a \u0646\u06a9\u0631\u062f\u0647\u200c\u0627\u06cc\u062f\u060c \u0646\u0627\u0645 \u0648 \u0646\u0627\u0645 \u062e\u0627\u0646\u0648\u0627\u062f\u06af\u06cc \u0648 \u0646\u0627\u0645 \u0645\u062d\u0635\u0648\u0644 \u0631\u0627 \u067e\u06cc\u0627\u0645\u06a9 \u06a9\u0646\u06cc\u062f \u062a\u0627\r\n \u0644\u06cc\u0646\u06a9\u200c\u0647\u0627 \u062f\u0648\u0628\u0627\u0631\u0647 \u0627\u0631\u0633\u0627\u0644 \u0634\u0648\u0646\u062f.<\/li>\r\n <\/ul>\r\n <p style=\"font-size: 16px; line-height: 1.8; margin-top: 15px;\"> \ud83d\udcac \u0631\u0627\u0647\u200c\u0647\u0627\u06cc \u0627\u0631\u062a\u0628\u0627\u0637\u06cc \u067e\u0634\u062a\u06cc\u0628\u0627\u0646\u06cc:<br> \u0648\u0627\u062a\u0633\u200c\u0627\u067e \u06cc\u0627 \u067e\u06cc\u0627\u0645\u06a9:\r\n <strong>09395106248<\/strong><br> \u062a\u0644\u06af\u0631\u0627\u0645: <strong>@ma_limbs<\/strong> <\/p>\r\n<\/div>\n","protected":false},"excerpt":{"rendered":"<p>\u062f\u0648\u0631\u0647 \u062c\u0627\u0645\u0639 \u062a\u0648\u0633\u0639\u0647 \u0627\u067e\u0644\u06cc\u06a9\u06cc\u0634\u0646\u200c\u0647\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc \u062f\u0631 Google Cloud Platform \u062f\u0648\u0631\u0647 \u062c\u0627\u0645\u0639 Google Cloud Platform: \u062a\u0648\u0633\u0639\u0647 \u0627\u067e\u0644\u06cc\u06a9\u06cc\u0634\u0646\u200c\u0647\u0627\u06cc \u067e\u0631\u062f\u0627\u0632\u0634 \u0632\u0628\u0627\u0646 \u0637\u0628\u06cc\u0639\u06cc \u0628\u0631\u0627\u06cc \u062a\u062d\u0644\u06cc\u0644 \u0627\u062d\u0633\u0627\u0633\u0627\u062a \u062f\u0631 \u0645\u0642\u06cc\u0627\u0633 \u0628\u0632\u0631\u06af\u060c \u0628\u0627 \u062f\u0642\u062a \u0628\u0627\u0644\u0627 \u0648 \u067e\u06cc\u0686\u06cc\u062f\u06af\u06cc \u067e\u06cc…<\/p>\n","protected":false},"featured_media":67493,"comment_status":"open","ping_status":"closed","template":"","meta":{"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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