Базовый шаблон интернет-магазина на Django

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Deep Learning Architectures: CNNs, RNNs, and GANs

1. Pooling Layers in CNNs

A pooling layer is a down-sampling layer in a Convolutional Neural Network (CNN) usually placed after a convolutional layer. It reduces the spatial dimensions (width × height) of the input feature maps while retaining the most critical structural information.

Types of Pooling Layers

  • Max Pooling: Extracts the maximum value from the region covered by the sliding filter. Purpose: Captures dominant features like sharp edges and bright pixels.
  • Average Pooling: Computes the average
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Fundamentals of AI: From Search to Expert Systems

UNIT I: Foundations of Artificial Intelligence

1. Introduction to Artificial Intelligence

Artificial Intelligence (AI) is a branch of computer science that focuses on creating machines capable of performing tasks that normally require human intelligence. These include learning, reasoning, problem-solving, decision-making, language understanding, and pattern recognition. AI simulates human thinking through algorithms and data processing, finding applications in robotics, virtual assistants, medical

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Supervised and Unsupervised Learning Model Reference

Supervised Classification

Logistic Regression (LR)

  • Type: Binary Classification
  • Scaling: Yes (StandardScaler)
  • Outliers: Not robust
  • Categorical Variables: No (encode first)
  • Core Idea: Sigmoid function maps output to 0–1 probability; threshold ≥ 0.5 predicts class 1.
  • Advantages: Fast, simple, interpretable, outputs probabilities.
  • Disadvantages: Binary only, requires linear boundary, fails on non-linear data.
  • Metrics: Accuracy, Precision, Recall, F1-Score, Confusion Matrix.

Decision Trees (DT)

  • Type: Classification
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Mastering Binary Trees, Searching, and Sorting Algorithms

Understanding Trees and Hierarchical Data

Trees can feel like a big jump from linear data structures like arrays or linked lists, but they are incredibly intuitive once you see how they organize data hierarchically. Here is a clear, scannable breakdown of the core concepts, representations, traversals, and Binary Search Tree (BST) operations you need to know.

1. Definitions and Core Concepts

A Tree is a non-linear, hierarchical data structure consisting of nodes connected by edges. It contains no cycles

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Mastering Stacks and Queues: Data Structure Fundamentals

1. What is a Stack?

A stack is a linear data structure that follows the LIFO (Last In, First Out) principle. Think of it like a stack of plates in a cafeteria: the last plate you place on top is the first one you take off.

2. Representation of a Stack

There are two primary ways to implement a stack in memory:

A. Array Representation (Static Allocation)

  • How it works: A fixed-size array is allocated, and a variable named top keeps track of the index of the topmost element.
  • Initial State: top = -1 (indicates
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