Explore all articles, grouped by publish date.
2026
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Model Compression via Knowledge Distillation
How knowledge distillation compresses teacher models into compact students by transferring behavior and using tailored training objectives for efficient models.
2025
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Low-Rank Adaptation (LoRA)
Explore how Low-Rank Adaptation (LoRA) enables efficient fine-tuning of LLMs through low-rank matrix decomposition and adaptive scaling.
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Mixture of Experts - Mathematical Foundations and Scaling
Explore how Mixture of Experts (MoE) architectures scale LLMs by routing tokens through specialized experts for greater efficiency and performance.
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The Equations That Changed The World
Let us look at equations that shaped the world as we know of today.
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DNS Architecture And DNS Records
In-depth exploration of the OSI model, with code snippets to illustrate each layer's function in networking.
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Activation And Loss Functions In Deep Learning
In this article we explore various Loss and Activation functions in deep learning
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AI and the Art of Subtle Control
Understanding the internal mechanics of LLMs involves exploring tokenization, attention mechanisms, transformers, training, and inference processes.
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Data Pipelines And Evolution of ETL vs ELT
A technical exploration of data pipeline components, governance, and a comparison between ETL and ELT methodologies.
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Understanding the Internal Mechanics of LLMs
Understanding the internal mechanics of LLMs involves exploring tokenization, attention mechanisms, transformers, training, and inference processes.
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Data Engineering on Google Cloud Platform (GCP)
An exploration of the essential components and best practices for data engineering on Google Cloud Platform.