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Russian translation
Dasha Andreeva edited this page Sep 24, 2022
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19 revisions
- Try to pick up all of the files from the same week. Most of the time, EN files from the same week are homogeneous in writers, topics, and style. We wish to keep the structure consistent also in the RU files. Especially if the RU translations are authored by different people, try to keep the translation of terms, particularly the technical and mathematical ones, consistent throughout the files.
- Try to keep the translation of terms consistent with the #Terms table below. If you're unsure about a translation, ask on Slack, have no fear :)
- After having completed the review, create another Pull Request. Write the PR number in the Notes column of the workload distribution, like so "Reviewed (#000)". When the PR is approved, write Review approved in the same column.
| File name | Translator | Start date | Publish date | Reviewers | PR | Notes |
|---|---|---|---|---|---|---|
README.md |
Evgeniy Pak | 23 Sep 2020 | 24 Sep 2020 | #624 | ||
index.md |
Evgeniy Pak | 23 Sep 2020 | 25 Sep 2020 | #624 | ||
01.md |
Evgeniy Pak | 23 Sep 2020 | 25 Sep 2020 | #624 | ||
01-1.md |
Evgeniy Pak | 23 Sep 2020 | 24 Sep 2020 | #624 | ||
01-2.md |
Evgeniy Pak | 25 Sep 2020 | 05 Oct 2020 | #653 | ||
01-3.md |
Evgeniy Pak | 25 Sep 2020 | 10 Oct 2020 | #666 | ||
lecture01.sbv |
Evgeniy Pak | |||||
practicum01.sbv |
Evgeniy Pak | |||||
02.md |
Daria Andreeva | |||||
02-1.md |
Daria Andreeva | |||||
02-2.md |
Daria Andreeva | |||||
02-3.md |
Daria Andreeva | |||||
lecture02.sbv |
Daria Andreeva | 24 Sep 2022 | ||||
practicum02.sbv |
Daria Andreeva | |||||
03.md |
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03-1.md |
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03-2.md |
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03-3.md |
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lecture03.sbv |
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practicum03.sbv |
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04.md |
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04-1.md |
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practicum04.sbv |
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05.md |
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05-1.md |
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05-2.md |
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05-3.md |
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lecture05.sbv |
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practicum05.sbv |
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06.md |
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06-1.md |
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07.md |
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08.md |
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09.md |
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09-3.md |
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10.md |
Kateryna Solonko | 25 Sep 2020 | ||||
10-1.md |
Kateryna Solonko | |||||
10-2.md |
Kateryna Solonko | |||||
10-3.md |
Kateryna Solonko | |||||
11.md |
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11-1.md |
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11-3.md |
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12.md |
Evgeniy Pak | 28 Nov 2020 | 03 Dec 2020 | #703 | ||
12-1.md |
Evgeniy Pak | 01 Dec 2020 | 03 Dec 2020 | #703 | ||
12-2.md |
Evgeniy Pak | 03 Dec 2020 | 04 Dec 2020 | #703 | ||
12-3.md |
Evgeniy Pak | 05 Dec 2020 | 05 Dec 2020 | #703 | ||
13.md |
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14.md |
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14-3.md |
| Term | Translation |
|---|---|
| Class | Урок |
| Lecture | Лекция |
| Practicum | Практикум |
| Term | Translation |
|---|---|
| activation | активация |
| activation function | функция активации |
| adaline | adaline |
| affine transformation | аффинное преобразование |
| (artificial) neural network | (искусственная) нейронная сеть |
| autoencoder | автокодировщик |
| autonomous vehicles | автономные транспортные средства |
| backpropagation | метод обратного распространения ошибки |
| batch normalization | пакетная нормализация |
| bias | смещение |
| chain rule | правило дифференцирования сложной функции |
| computer vision | компьютерное зрение |
| contrast normalization | контрастная нормализация |
| convolution | свёртка |
| cost function | функция стоимости |
| cybernetic | кибернетика |
| deep-learning | глубокое обучение |
| dropout | дропаут |
| embedding | представление |
| energy-based model | энергетическая модель |
| ensemble | ансамбль |
| feature | признак |
| fire (of neuron) | активация |
| fully connected layer | полносвязный слой |
| fully connected network | полносвязная сеть |
| gradient | градиент |
| gradient descent | градиентный спуск |
| hidden layer | скрытый слой |
| hierarchical representation | иерархическое представление |
| image classification | классификация изображений |
| image segmentation | сегментация изображений |
| inference | вывод |
| Jacobian matrix | матрица Якоби |
| Jupyter Notebook | Jupyter Notebook |
| label | метка |
| lane tracking | отслеживание полосы дорожного движения |
| latent space | скрытое пространство |
| layer | слой |
| layers | слои |
| lecture part A | лекция часть A |
| logistic regression | логистическая регрессия |
| loss function | функция потерь |
| Nash equilibrium | Равновесие Нэша |
| natural language understanding | понимание естественного языка |
| natural language processing | обработка естественного языка |
| nearest neighbor | ближайший сосед |
| non-maximum suppression | подавление немаксимумов |
| norm | норма |
| object detection | обнаружение объектов |
| one-hot | унитарный код |
| parameter | параметр |
| pattern recognition | распознавание образов |
| perceptron | перцептрон |
| pooling | субдискретизация |
| practicum | практикум |
| recurrent neural networks | рекуррентные нейронные сети |
| reflection | отражение |
| regularization | регуляризация |
| rotation | вращение |
| scaling | масштабирование |
| self-supervised learning | самостоятельное обучение |
| scalar | скаляр |
| semantic segmentation | семантическая сегментация |
| shearing | сдвиг |
| softmax, soft (arg)max | softmax, soft (arg)max |
| speech recognition | распознавание речи |
| stochastic gradient descent | стохастический градиентный спуск |
| supervised learning | обучение с учителем |
| tensor | тензор |
| translation | перемещение |
| trajectory | траектория |
| unsupervised learning | обучение без учителя |
| visual cortex | зрительная кора |
| weight | вес |
| weighted sum | взвешенная сумма |
| Term | Explanation |
|---|---|
| actor critic | |
| CNN | Convolutional Neural Network |
| GAN | generative adversarial networks |
| GPU | Graphic Processing Unit |
| ReLU | Rectified linear unit |