server/index.js

@@ -42,7 +42,6 @@ app.use(require('./root'))
 /**
  * Добавляйте сюда свои routers.
  */
-app.use('/kfu-m-24-1', require('./routers/kfu-m-24-1'))
 app.use('/epja-2024-1', require('./routers/epja-2024-1'))
 app.use('/todo', require('./routers/todo/routes'))
 app.use('/dogsitters-finder', require('./routers/dogsitters-finder'))

server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaries.json

@@ -1,12 +0,0 @@
-[
-  {
-    "id": 0,
-    "description": "1000 часто используемых",
-    "imageFilename": "kart1.jpg"
-  },
-  {
-    "id": 1,
-    "description": "10 слов в Data Science",
-    "imageFilename": "kart1.jpg"
-  }
-]

server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaryWords.json

@@ -1,150 +0,0 @@
-[
-  {
-    "id": 0,
-    "words": [
-      {
-        "id": 0,
-        "word": "Tech",
-        "definition": "short for technical, relating to the knowledge, machines, or methods used in science and industry. Tech is a whole industry, which includes IT",
-        "examples": [
-          "“As a DevOps engineer I have been working in Tech since 2020.”"
-        ],
-        "synonyms": ["IT"]
-      },
-      {
-        "id": 1,
-        "word": "career path",
-        "definition": "the series of jobs or roles that constitute a person's career, especially one in a particular field",
-        "examples": [
-          "“Technology is an evolving field with a variety of available career paths.”"
-        ],
-        "synonyms": []
-      }
-    ]
-  },
-  {
-    "id": 1,
-    "words": [
-      {
-        "id": 0,
-        "word": "Machine Learning",
-        "translation": "Машинное обучение",
-        "definition": "An approach to artificial intelligence where computers learn from data without being explicitly programmed.",
-        "synonyms": ["Trainable Algorithms", "Automated Learning"],
-        "examples": [
-          "We used machine learning techniques to forecast product demand.",
-          "The movie recommendation system is based on machine learning algorithms.",
-          "Machine learning helped improve the accuracy of speech recognition in our application."
-        ]
-      },
-      {
-        "id": 1,
-        "word": "Neural Network",
-        "translation": "Нейронная сеть",
-        "definition": "A mathematical model inspired by the structure and function of biological neural networks, consisting of interconnected nodes organized in layers that can process information.",
-        "synonyms": ["Artificial Neural Network", "Deep Neural Network"],
-        "examples": [
-          "To process large amounts of data, we created a deep learning neural network.",
-          "This neural network is capable of generating realistic images.",
-          "Using neural networks significantly improved the quality of text translation."
-        ]
-      },
-      {
-        "id": 2,
-        "word": "Algorithm",
-        "translation": "Алгоритм",
-        "definition": "A step-by-step procedure or set of instructions for solving a problem or performing a computation.",
-        "synonyms": ["Procedure", "Method"],
-        "examples": [
-          "The algorithm we developed quickly finds the optimal delivery route.",
-          "This algorithm sorts an array with a minimal number of operations.",
-          "Encryption algorithms ensure secure transmission of data over the internet."
-        ]
-      },
-      {
-        "id": 3,
-        "word": "Data Model",
-        "translation": "Модель данных",
-        "definition": "An abstract representation of the structure of data, describing how data is organized and related to each other.",
-        "synonyms": ["Data Structure", "Schema"],
-        "examples": [
-          "Our data model allows us to efficiently manage relationships between customers and orders.",
-          "The data model was designed considering scalability and performance requirements.",
-          "This data model is used for storing information about social network users."
-        ]
-      },
-      {
-        "id": 4,
-        "word": "Regression",
-        "translation": "Регрессия",
-        "definition": "A statistical method used to determine the relationship between one variable and others.",
-        "synonyms": ["Linear Regression", "Nonlinear Regression"],
-        "examples": [
-          "We applied linear regression to analyze the impact of advertising campaigns on sales.",
-          "Results from the regression analysis showed a strong correlation between customer age and purchase frequency.",
-          "Regression helped us assess how changes in environmental conditions affect crop yield."
-        ]
-      },
-      {
-        "id": 5,
-        "word": "Clustering",
-        "translation": "Кластеризация",
-        "definition": "The process of grouping similar objects into clusters so that objects within the same cluster are more similar to each other than to those in other clusters.",
-        "synonyms": ["Grouping", "Segmentation"],
-        "examples": [
-          "Clustering allowed us to divide customers into several groups according to their purchasing behavior.",
-          "Clustering methods are used to automatically group news by topic.",
-          "As a result of clustering, several market segments were identified, each with its own characteristics."
-        ]
-      },
-      {
-        "id": 6,
-        "word": "Supervised Learning",
-        "translation": "Обучение с учителем",
-        "definition": "A type of machine learning where the algorithm learns from labeled data, meaning data for which correct answers are known.",
-        "synonyms": ["Controlled Learning", "Labeled Classification"],
-        "examples": [
-          "Supervised learning is used to classify emails as spam or not-spam.",
-          "This approach was used to create a model that predicts real estate prices based on multiple parameters.",
-          "Supervised learning helps diagnose diseases at early stages through medical data analysis."
-        ]
-      },
-      {
-        "id": 7,
-        "word": "Data Labeling",
-        "translation": "Разметка данных",
-        "definition": "The process of assigning labels or classes to data so it can be used in supervised learning.",
-        "synonyms": ["Data Annotation", "Tagging"],
-        "examples": [
-          "Before starting model training, we labeled the data by assigning each photo an animal category.",
-          "Data labeling includes marking user reviews as positive or negative.",
-          "Text documents were labeled with special tags for subsequent analysis."
-        ]
-      },
-      {
-        "id": 8,
-        "word": "Hyperparameters",
-        "translation": "Гиперпараметры",
-        "definition": "Parameters that define the structure and behavior of a machine learning model, set before the learning process begins.",
-        "synonyms": ["Model Settings", "Configuration Parameters"],
-        "examples": [
-          "Optimizing hyperparameters enabled us to enhance the performance of our machine learning model.",
-          "Hyperparameters include settings such as the number of layers in a neural network and the learning rate.",
-          "Choosing the right hyperparameters is crucial for achieving high model accuracy."
-        ]
-      },
-      {
-        "id": 9,
-        "word": "Model Validation",
-        "translation": "Валидация модели",
-        "definition": "The process of evaluating the quality of a model by testing it on new, previously unseen data.",
-        "synonyms": ["Model Testing", "Model Verification"],
-        "examples": [
-          "After completing the training, we validated the model using a test dataset.",
-          "During model validation, its ability to make accurate predictions on new data is checked.",
-          "Validation showed that the model is robust against changes in data and has low generalization error."
-        ]
-      }
-    ]
-  }
-]

server/routers/kfu-m-24-1/eng-it-lean/dictionaries/index.js

@@ -1,21 +0,0 @@
-const router = require("express").Router();
-
-module.exports = router;
-
-const data = require("./data/dictionaries.json");
-const wordsData = require("./data/dictionaryWords.json");
-
-router.get("/", (req, res) => {
-  res.send(data);
-});
-
-router.get("/:id", (req, res) => {
-  const id = parseInt(req.params.id);
-  const words = wordsData.find((word) => word.id === id);
-
-  if (!words) {
-    return res.status(404).send("Not found");
-  }
-
-  res.send(words);
-});

server/routers/kfu-m-24-1/eng-it-lean/index.js

@@ -1,13 +0,0 @@
-const router = require("express").Router();
-
-const dictionariesRouter = require("./dictionaries");
-module.exports = router;
-
-const delay =
-  (ms = 1000) =>
-  (req, res, next) => {
-    setTimeout(next, ms);
-  };
-
-router.use(delay());
-router.use("/dictionaries", dictionariesRouter);

server/routers/kfu-m-24-1/index.js

@@ -1,7 +0,0 @@
-const { Router } = require('express')
-const router = Router()
-
-router.use('/eng-it-lean', require('./eng-it-lean/index'))
-
-module.exports = router
-