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# Искусственный интеллект

[Old Version](Historic/README_ru.md)
[Old English Version](Historic/README.md)

Этот репозиторий содержит материалы к курсу "Искусственный интеллект", разработанные [Дмитрием Сошниковым](https://soshnikov.com).

### Содержание

**Введение в ИИ**
* Представление знаний [[notebook](01-IntroAI/02-KnowledgeRep/knowledgebase.ipynb)], [[video](https://youtu.be/IukbYvzHh2I)]
* Генетические алгоритмы [[notebook](01-IntroAI/03-Genetic/Genetic.ipynb)], [[lab](01-IntroAI/03-Genetic/Lab/README.md)]

**Машинное обучение (полная версия)**
* Регрессия [[notebook](02-ML/01-Regression/Regression.ipynb)], [[lab](02-ML/01-Regression/Lab/README.md)]
* Классификация [[notebook](02-ML/02-Classification/Classification.ipynb)], [[lab](02-ML/02-Classification/Lab/README.md)]
* Кластеризация [[notebook](02-ML/03-Clustering/Clustering.ipynb)], [[lab](02-ML/03-Clustering/Lab/README.md)], [[seminar](02-ML/03-Clustering/Lab/ML_Seminar_Clustering_Problem.ipynb)]

**Машинное обучение (краткая версия)**
* Введение в машинное обучение [[notebook](02-MLExpress/ExpressML.ipynb)], [[video](https://youtu.be/qqRXepJgirc)]

**Нейросети**
* Персептрон [[notebook](03-NeuralNetworks/01-Perceptron/Perceptron.ipynb)], [[lab](03-NeuralNetworks/01-Perceptron/Lab/README.md)]
* Разрабатываем свой фреймворк [[notebook](03-NeuralNetworks/01-Perceptron/MultiLayerPerceptron.ipynb)], [[video](https://youtu.be/4UBinNtTMIs?si=MvQdDOtYEgrVp78k)]
* TensorFlow и Keras [[notebook](03-NeuralNetworks/02-TensorFlow/IntroKerasTF.ipynb)], [[video](https://youtu.be/q-e0RVzyHcI?si=BtIko2AzyHsrbQAe)] [[семинар](03-NeuralNetworks/02-TensorFlow/KerasTF-Seminar.ipynb)], [[lab](03-NeuralNetworks/02-TensorFlow/Lab/README.md)]
* PyTorch [[video](https://www.youtube.com/watch?v=PDj3eezIfF0)], [[seminar](03-NeuralNetworks/03-PyTorch/PyTorch_Seminar.ipynb)]

**Компьютерное зрение**
* Введение в CV [[работа с изображениями](04-CV/01-IntroCV/ImageLibs.ipynb)], [[сервис Imagga](04-CV/01-IntroCV/Imagga.ipynb)], [[анализ фото](04-CV/01-IntroCV/PhotoAnalysis.ipynb)]
* OpenCV [[notebook](04-CV/02-OpenCV/OpenCV.ipynb)], [[семинар](04-CV/02-OpenCV/Seminar_CV.ipynb)], [[пример](04-CV/02-OpenCV/FaceLandmarks.ipynb)]
* Свёрточные сети [[notebook](04-CV/03-CNN/ConvolutionNetworks.ipynb)], [[video](https://www.youtube.com/watch?v=_5BfkVGynGg)],[[dropout](04-CV/03-CNN/Dropout.ipynb), [[lab](04-CV/03-CNN/Lab/README.md)]
* Transfer Learning [[notebook](04-CV/04-TransferLearning/TransferLearning.ipynb)], [[video](https://youtu.be/7LVtBU-uPEQ)], [[визуализация CNN](04-CV/04-TransferLearning/CNN_Visualzation.ipynb)], [[дорожные знаки](04-CV/04-TransferLearning/RoadSignes.ipynb)], [[lab](04-CV/04-TransferLearning/Lab/README.md)]
* Object Detection [[notebook](04-CV/05-ObjectDetection/ObjectDetection.ipynb)]
* Semantic Segmentation [[notebook]](04-CV/06-Segmentation/SemanticSegmentation.ipynb), [[seminar](04-CV/06-Segmentation/SegmentationSeminar.ipynb)]
* Autoencoders [[notebook](04-CV/07-AutoEncodersGAN/AutoencodersTF.ipynb)], [[noisy digits](04-CV/07-AutoEncodersGAN/NoisyDigits.ipynb), [[video](https://youtu.be/-36H-NNJMTw)]
* GANs [[notebook](04-CV/07-AutoEncodersGAN/GANTF.ipynb), [[seminar](04-CV/07-AutoEncodersGAN/Segmentation_AE_GAN.ipynb)], [[video](https://youtu.be/M4na17KhAAY)]

**Обработка естественного языка**
* Введение в NLP [[notebook](05-NLP/01-IntroNLP/MeaningCloud.ipynb)], [[lab](05-NLP/01-IntroNLP/Lab/README.md)]
* BoW, TF-IDF [[notebook](05-NLP/02-BoW-TFIDF/TextRepresentation.ipynb)], [[lab](05-NLP/02-BoW-TFIDF/Lab/README.md)]
* Embeddings [[notebook](05-NLP/03-Embeddings/Embeddings.ipynb)], [[CBoW](05-NLP/03-Embeddings/CBoW.ipynb)], [[lab](05-NLP/03-Embeddings/Lab/README.md)]
* Рекуррентные сети [[notebook](05-NLP/04-RNNs/RNN.ipynb)], [[генеративные сети](05-NLP/04-RNNs/GenerativeRNN.ipynb)], [[NER](05-NLP/04-RNNs/NER.ipynb)], [[lab](05-NLP/04-RNNs/Lab/README.md)]
* Трансформеры [[notebook](05-NLP/05-Transformers/Transformers.ipynb)], [[HuggingFace](05-NLP/05-Transformers/HuggingFace.ipynb)]
* Мультимодальные модели [[Stable Diffusion](05-NLP/06-MultiModal/StableDiffusionExplore.ipynb)]

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