From 872c921a536ce8a25f9c02b8331f2e263049da3c Mon Sep 17 00:00:00 2001 From: qosquo Date: Thu, 19 Dec 2024 19:51:07 +0300 Subject: [PATCH] feat: add kfu-m-24-1 stubs folder; include eng-it-lean stubs api --- server/index.js | 1 + .../dictionaries/data/dictionaries.json | 12 ++ .../dictionaries/data/dictionaryWords.json | 150 ++++++++++++++++++ .../eng-it-lean/dictionaries/index.js | 21 +++ .../routers/kfu-m-24-1/eng-it-lean/index.js | 13 ++ server/routers/kfu-m-24-1/index.js | 7 + 6 files changed, 204 insertions(+) create mode 100644 server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaries.json create mode 100644 server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaryWords.json create mode 100644 server/routers/kfu-m-24-1/eng-it-lean/dictionaries/index.js create mode 100644 server/routers/kfu-m-24-1/eng-it-lean/index.js create mode 100644 server/routers/kfu-m-24-1/index.js diff --git a/server/index.js b/server/index.js index 0be67f2..df0bd55 100644 --- a/server/index.js +++ b/server/index.js @@ -42,6 +42,7 @@ 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')) diff --git a/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaries.json b/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaries.json new file mode 100644 index 0000000..cf5e736 --- /dev/null +++ b/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaries.json @@ -0,0 +1,12 @@ +[ + { + "id": 0, + "description": "1000 часто используемых", + "imageFilename": "kart1.jpg" + }, + { + "id": 1, + "description": "10 слов в Data Science", + "imageFilename": "kart1.jpg" + } +] diff --git a/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaryWords.json b/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaryWords.json new file mode 100644 index 0000000..8c22e36 --- /dev/null +++ b/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/data/dictionaryWords.json @@ -0,0 +1,150 @@ +[ + { + "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." + ] + } + ] + } +] diff --git a/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/index.js b/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/index.js new file mode 100644 index 0000000..ab86b1b --- /dev/null +++ b/server/routers/kfu-m-24-1/eng-it-lean/dictionaries/index.js @@ -0,0 +1,21 @@ +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); +}); diff --git a/server/routers/kfu-m-24-1/eng-it-lean/index.js b/server/routers/kfu-m-24-1/eng-it-lean/index.js new file mode 100644 index 0000000..702db37 --- /dev/null +++ b/server/routers/kfu-m-24-1/eng-it-lean/index.js @@ -0,0 +1,13 @@ +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); diff --git a/server/routers/kfu-m-24-1/index.js b/server/routers/kfu-m-24-1/index.js new file mode 100644 index 0000000..ce92d39 --- /dev/null +++ b/server/routers/kfu-m-24-1/index.js @@ -0,0 +1,7 @@ +const { Router } = require('express') +const router = Router() + +router.use('/eng-it-lean', require('./eng-it-lean/index')) + +module.exports = router + -- 2.45.2