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1. Algebraic System

An algebraic system is a non-empty set together with one or more operations (like addition or multiplication) defined on it.
Example: A set AAA with an operation ∗*∗ is written as (A,∗)(A, *)(A,∗).


2. Semigroup

A semigroup is a set SSS with a binary operation ∗*∗ that is associative:

(a∗b)∗c=a∗(b∗c),∀a,b,c∈S(a * b) * c = a * (b * c), \quad \forall a,b,c \in S(a∗b)∗c=a∗(b∗c),∀a,b,c∈S


3. Monoid

A monoid is a semigroup that has an identity element eee,

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BASIC DEFINITIONS

Static Website

Fixed content, same for all users, no server processing

Dynamic Website

Content changes based on user/data, uses backend

Web Application

Interactive software running in browser (like Gmail)

Frontend vs Backend

Frontend → UI (HTML, CSS, JS)

Backend → Server, database, logic

Full Stack Development

Working on both frontend + backend

SPA (Single Page Application)

Loads one page, updates content dynamically

Advantages of SPA

Fast, smooth UX, less reload, better performance

🔹 NODE.

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Natural Language Processing: Meaning Representation and Parsing

1. Meaning Representation in NLP

Meaning representation in Natural Language Processing (NLP) refers to the process of converting natural language into a formal structure that a machine can understand and reason about. It involves representing the semantics of words, phrases, and sentences using logical forms, semantic networks, frames, or predicate logic. The goal is to capture the intended meaning of a sentence rather than just its syntactic structure.

The need for meaning representation arises because

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Regression and Segmentation are two important analytical approaches used in data science. Regression is used to predict continuous numerical values, such as sales, profit, or temperature. It establishes a relationship between dependent and independent variables. On the other hand, Segmentation (often linked with clustering) is used to group similar data points into distinct categories based on patterns, such as customer segmentation in marketing.Supervised and Unsupervised learning are the two main

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Essential Data Science and Analytics Concepts

Data Architecture and Analytics Fundamentals

  • Data Architecture: The structured design of data systems, defining collection, storage, integration, and management for efficient use.
  • Sensor Data: Information collected automatically from devices measuring physical conditions like temperature, pressure, motion, or environmental changes.
  • Outliers: Data points significantly different from other observations, often caused by errors, variability, or rare, unusual events.
  • Duplicate Data: Repeated records within
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Compiler Design: Parsing, Optimization, and Memory Management

Top-Down vs. Bottom-Up Parsing

Bottom-up parsing starts from the input string and reduces it to the start symbol (leaves → root). Example: LR parsing.

Top-down parsing is simple but less powerful, while bottom-up is complex but handles more grammars.

FIRST Algorithm

  • If X is terminal → FIRST(X) = {X}
  • If X → ε → include ε
  • If X → Y₁Y₂…Yₙ:
    • Add FIRST(Y₁) (except ε)
    • If ε in FIRST(Y₁), check next
    • If all have ε → add ε
  • Repeat until no change

FOLLOW Algorithm

  • Put $ in FOLLOW(Start Symbol)
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