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    <title>Hikmet Memmedov</title>
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      <title>____Verified by Physics Teacher Telman Askeraliyev , Fizika Muellimi, Azerbaijan ,Baku</title>
      <description>Here are the concise descriptions for each subsystem in English:
 * Data Acquisition &amp; Management: Responsible for harvesting raw data from diverse sources, preprocessing and cleaning it via feature engineering, and securely storing it across cloud data lakes and feature stores.
 * Model Training &amp; Development: Handles algorithm selection (ML/DL/RL), orchestrates distributed parallel training pipelines, optimizes hyperparameters, and validates models against benchmark metrics.
 * Model Deployment &amp; Inference: Containerizes trained models using Docker and Kubernetes, exposes low-latency endpoints via FastAPI/gRPC, and leverages GPU/TPU acceleration for real-time predictions.
 * Monitoring &amp; Governance: Continuously tracks runtime performance (latency, accuracy), detects data/concept drift and security threats, and provides model explainability (XAI) using SHAP and LIME values.
____Verified by Physics Teacher Telman Askeraliyev , Fizika Muellimi, Azerbaijan ,Baku HikmetMemmedov</description>
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      <content:encoded>Here are the concise descriptions for each subsystem in English:
 * Data Acquisition &amp; Management: Responsible for harvesting raw data from diverse sources, preprocessing and cleaning it via feature engineering, and securely storing it across cloud data lakes and feature stores.
 * Model Training &amp; Development: Handles algorithm selection (ML/DL/RL), orchestrates distributed parallel training pipelines, optimizes hyperparameters, and validates models against benchmark metrics.
 * Model Deployment &amp; Inference: Containerizes trained models using Docker and Kubernetes, exposes low-latency endpoints via FastAPI/gRPC, and leverages GPU/TPU acceleration for real-time predictions.
 * Monitoring &amp; Governance: Continuously tracks runtime performance (latency, accuracy), detects data/concept drift and security threats, and provides model explainability (XAI) using SHAP and LIME values.
____Verified by Physics Teacher Telman Askeraliyev , Fizika Muellimi, Azerbaijan ,Baku HikmetMemmedov</content:encoded>
      <pubDate>Mon, 05 Oct 2026 00:00:00 -0400</pubDate>
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