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[
  {
    "timestamp": "2026-10-21",
    "url": "https:\/\/github.com\/TheAlgorithms\/Python\/blob\/master\/machine_learning\/automatic_differentiation.py?raw=true",
    "id": "63476337@machine_learning\/automatic_differentiation.py",
    "code_language": "Python",
    "code": [
      "\u0022\u0022\u0022",
      "Demonstration of the Automatic Differentiation (Reverse mode).",
      "",
      "Reference: https:\/\/en.wikipedia.org\/wiki\/Automatic_differentiation",
      "",
      "Author: Poojan Smart",
      "Email: [email protected]",
      "\u0022\u0022\u0022"
    ],
    "num_lines": 329,
    "user_name": "TheAlgorithms",
    "user_url": null
  },
  {
    "timestamp": "2026-10-21",
    "url": "https:\/\/github.com\/TheAlgorithms\/Python\/blob\/master\/machine_learning\/polynomial_regression.py?raw=true",
    "id": "63476337@machine_learning\/polynomial_regression.py",
    "code_language": "Python",
    "code": [
      "\u0022\u0022\u0022",
      "Polynomial regression is a type of regression analysis that models the relationship",
      "between a predictor x and the response y as an mth-degree polynomial:",
      "",
      "y = β₀ + β₁x + β₂x² + ... + βₘxᵐ + ε",
      "",
      "By treating x, x², ..., xᵐ as distinct variables, we see that polynomial regression is a",
      "special case of multiple linear regression. Therefore, we can use ordinary least squares"
    ],
    "num_lines": 213,
    "user_name": "TheAlgorithms",
    "user_url": null
  },
  {
    "timestamp": "2026-10-21",
    "url": "https:\/\/github.com\/TheAlgorithms\/Python\/blob\/master\/computer_vision\/haralick_descriptors.py?raw=true",
    "id": "63476337@computer_vision\/haralick_descriptors.py",
    "code_language": "Python",
    "code": [
      "\u0022\u0022\u0022",
      "https:\/\/en.wikipedia.org\/wiki\/Image_texture",
      "https:\/\/en.wikipedia.org\/wiki\/Co-occurrence_matrix#Application_to_image_analysis",
      "\u0022\u0022\u0022",
      "",
      "import imageio.v2 as imageio",
      "import numpy as np",
      "import numpy.typing as npt"
    ],
    "num_lines": 435,
    "user_name": "TheAlgorithms",
    "user_url": null
  },
  {
    "timestamp": "2026-10-21",
    "url": "https:\/\/github.com\/TheAlgorithms\/Python\/blob\/master\/electronics\/resistor_color_code.py?raw=true",
    "id": "63476337@electronics\/resistor_color_code.py",
    "code_language": "Python",
    "code": [
      "\u0022\u0022\u0022",
      "Title : Calculating the resistance of a n band resistor using the color codes",
      "",
      "Description :",
      "  Resistors resist the flow of electrical current.Each one has a value that tells how",
      "  strongly it resists current flow.This value\u0027s unit is the ohm, often noted with the",
      "  Greek letter omega: Ω.",
      ""
    ],
    "num_lines": 374,
    "user_name": "TheAlgorithms",
    "user_url": null
  },
  {
    "timestamp": "2026-10-21",
    "url": "https:\/\/github.com\/TheAlgorithms\/Python\/blob\/master\/maths\/keith_number.py?raw=true",
    "id": "63476337@maths\/keith_number.py",
    "code_language": "Python",
    "code": [
      "\u0022\u0022\u0022",
      "== Keith Number (Repfigit Number) ==",
      "A Keith number (also known as a repfigit number, short for \u0022repetitive",
      "Fibonacci-like digit\u0022) is a natural number n with d \u003E= 2 decimal digits",
      "such that when a sequence is formed starting with the d digits of n and each",
      "subsequent term is the sum of the preceding d terms, the number n itself",
      "appears in the sequence.",
      ""
    ],
    "num_lines": 184,
    "user_name": "TheAlgorithms",
    "user_url": null
  }
]