Wireless Channel

Wireless CommunicationLeave a Comment on Wireless Channel
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

Wireless CommunicationLeave a Comment on Network Coding Type – Opportunistic
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

Calculus – Transcendental Functions

Calculus, Mathematics, UncategorizedLeave a Comment on Calculus – Transcendental Functions
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.

Large Language ModelsLeave a Comment on Transformer Part I – Theory, Original Paper etc.
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

Large Language ModelsLeave a Comment on LM, N-Grams, RNNs, LLM, Fine Tuning, LoRA, QLoRA – Part III
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

Large Language ModelsLeave a Comment on LM, N-Grams, RNNs, LLM, Fine Tuning, LoRA, QLoRA – Part II
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
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