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CS Programming- AI and ML
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Computer Science Channel: Artificial Intelligence, Machine Learning, Deep Learning, Python and DataSciencefor advanced users.
Computer Science Channel: Artificial Intelligence, Machine Learning, Deep Learning, Python and DataSciencefor advanced users.
🧠 The channel focuses on advanced computer science topics: artificial intelligence, machine learning, deep learning, computer vision, and Data Science.
🐍 Particular attention is paid to Python — The key language for complex projects. It deals with algorithms, neural networks, data processing and practical applications in real problems.
📊 Useful for students, researchers and professionals. Materials help to deepen knowledge, master modern frameworks and apply them in practice in projects on AI and data analysis.
Connection Pool Sizing, Measured: Why 48 Connections Beat 400 A benchmark sweep of a PostgreSQL instance from 1 to 400 connections shows throughput peaking at 48 connections (18,039 tps) and dropping 37% by 400 connections, while average latency multiplied 13x. The piece explains why connections are OS processes competing for cores rather than free capacity, tests the Universal Scalability Law fit (R²=0.94, predicted optimum 45.1), evaluates the (cores×2)+spindles formula (predicts 9, far off the measured 48), and finds that synchronous_commit=off raises throughput but does not shift the peak. It closes with practical guidance: watch queue depth (cl_waiting in PgBouncer, pending-threads in HikariCP) rather than connection count, account for instances × pool size multiplication, and use transaction pooling or RDS Proxy for Lambda to avoid connection exhaustion.
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