ComputingNotes

Wireless Channel

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References: What is wireless channel? In wireless communication, a wireless channel refers to the physical medium, the air or space, through which electromagnetic signals travel from a transmitter to a receiver. Unlike a wired connection (like fiber optics or Ethernet cables) where the signal is contained within a physical “pipe,” a wireless channel is open ... Read More

Network Coding Type – Opportunistic

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References: What is opportunistic network coding? In the world of wireless communication, the biggest challenge isn’t just sending data, it’s doing so without creating a digital traffic jam. While traditional routers simply act as relay stations, a more intelligent approach has emerged: Opportunistic Network Coding. Instead of treating every packet as a solo traveler, we ... Read More

A Guide to Network Coding

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References: What is Network Coding? In traditional networking, routers act like simple relay stations i.e. they receive a packet and forward it toward its destination. However, this “forwarding-only” approach creates physical bottlenecks that limit how much data a network can handle. Network coding is a revolutionary paradigm that changes this by allowing routers to “mix” ... Read More

Data Structure and Algorithms – Array

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Resources: Array Array is one of the most fundamental and widely used data structures. It serves as a building block for more complex structures like heaps, hash tables, and matrices. 1. What is an Array? An array is a collection of items stored at contiguous memory locations. The idea is to store multiple items of ... Read More

Calculus – Transcendental Functions

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References: Transcendental Functions In mathematics, a transcendental function is a function that does not satisfy a polynomial equation with polynomial coefficients. To put it simply: it is any function that is not algebraic. While algebraic functions can be constructed using a finite number of elementary operations (addition, subtraction, multiplication, division, and taking roots), transcendental functions ... Read More

Transformer Part I – Theory, Original Paper etc.

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Resources: Transformer ‌Transformer is an encoder and decoder model. It uses a mechanism called Attention. Transformer model consists of encoder and decoder. Analogy Imagine you are at a loud party. You hear fragments of conversations. To understand a specific sentence, your brain does three things instantly: Transformer Architecture The Transformer architecture is an Encoder-Decoder structure. ... Read More

LM, N-Grams, RNNs, LLM, Fine Tuning, LoRA, QLoRA – Part III

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LLMs: Fine-tuninghttps://developers.google.com/machine-learning/crash-course/llm/tuning Foundation Models A Foundation LLM (or base/pre-trained model) is a general-purpose model trained on vast amounts of data. It understands grammar and can perform creative tasks like writing poetry. However, to solve specific problems (like classification or regression), it often serves as a starting platform rather than a finished solution. Fine Tuning Fine-tuning ... Read More

LM, N-Grams, RNNs, LLM, Fine Tuning, LoRA, QLoRA – Part II

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Introduction to Large Language Modelshttps://developers.google.com/machine-learning/crash-course/llm LLMs: What is a Large Language Model? An LLM is a predictive technology that estimates the next “token” (word, character, or subword) in a sequence. They outperform older models (like N-grams) because they use vastly more parameters and can process significantly more context at once. Transformer It is most successful ... Read More

LM, N-Grams, RNNs, LLM, Fine Tuning, LoRA, QLoRA – Part I

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Introduction to Large Language Modelshttps://developers.google.com/machine-learning/crash-course/llm What is Language Model? At its simplest, a language model is a statistical tool that predicts the next piece of text in a sequence. The N-gram Approach Early language models used “N-grams,” which are simply ordered sequences of words where N represents the number of words. Context Context refers to ... Read More
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