Seminars

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Занятия по Machine Learning клуба AI Community Innopolis

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- - seminar-1-1-python.ipynb
  - seminar-1-2-numpy.ipynb
- - seminar-2-1-math-background.ipynb
  - seminar-2-2-numpy.ipynb
  - seminar-2-3-rotation.ipynb
  - seminar-2-4-homework.ipynb
  - seminar-2-5-homework-solution.ipynb
- - seminar-3-1-pandas.ipynb
  - seminar-3-2-ml-intro.ipynb
  - seminar-3-3-linreg-math.ipynb
  - seminar-3-4-contest-baseline.ipynb
- - seminar-4-1-trees-theory.ipynb
  - seminar-4-2-trees-practice.ipynb
  - seminar-4-3-contest-baseline.ipynb
- - seminar-5-1-pca.ipynb
  - seminar-5-2-t-sne.ipynb
  - seminar-5-3-homework.ipynb
- - seminar-6-1-sgd-theory.ipynb
  - seminar-6-2-sgd-practice.ipynb
  - seminar-6-3-intro-nn.ipynb
  - seminar-6-4-homework.ipynb
- - seminar-7-1-nn-layers.ipynb
  - seminar-7-2-convolution.ipynb
  - seminar-7-3-nn-practice.ipynb
  - utils.py
- - seminar-8-1-color-spaces.ipynb
  - seminar-8-2-shape-detection.ipynb
  - seminar-8-3-contest-baseline.ipynb
  - Seminar_8.1-Figures.ipynb
- - .DS_Store
  - seminar-9-1-detection-tracking.ipynb
  - seminar-9-2-face-detection.ipynb
- - seminar-1-1-python.ipynb
  - seminar-1-2-numpy.ipynb
- - seminar-2-1-math-background.ipynb
  - seminar-2-2-numpy.ipynb
  - seminar-2-3-rotation.ipynb
  - seminar-2-4-homework.ipynb
  - seminar-2-5-homework-solution.ipynb
- - seminar-3-1-pandas.ipynb
  - seminar-3-2-ml-intro.ipynb
  - seminar-3-3-linreg-math.ipynb
  - seminar-3-4-contest-baseline.ipynb
- - 4-5-0-slides.pdf
  - 4-5-1-trees-theory.ipynb
  - 4-5-2-ensembling.ipynb
  - 4-5-3-rf-tuning.ipynb
- - seminar-5-1-pca.ipynb
  - seminar-5-2-t-sne.ipynb
  - seminar-5-3-homework-optional.ipynb
- - seminar-6-1-perceptron.ipynb
  - seminar-6-2-perceptron-practice.ipynb
  - seminar-6-3-intro-to_backprop.ipynb
  - seminar-6-4-homework.ipynb
- - seminar-7-1-nn-layers.ipynb
  - seminar-7-2-convolution.ipynb
  - seminar-7-3-nn-practice.ipynb
  - utils.py
- - seminar-8-1-color-spaces.ipynb
  - seminar-8-2-shape-detection.ipynb
- - seminar-1-1-python.ipynb
  - seminar-1-2-numpy.ipynb
  - seminar-1-3-pandas.ipynb
  - seminar-1-4-drawing_numpy.ipynb
- - seminar-10-1-slides.pdf
  - seminar-10-2-slides.pdf
- - seminar-2-1-math-background.ipynb
  - seminar-2-2-numpy.ipynb
  - seminar-2-3-rotation.ipynb
  - seminar-2-4-homework.ipynb
  - seminar-2-5-homework-solution.ipynb
- - seminar-3-1-ml-intro.ipynb
  - seminar-3-2-KNN-LinReg.pdf
  - seminar-3-3-linreg-math.ipynb
  - seminar-3-4-contest-baseline.ipynb
- - seminar-4-1-logreg.ipynb
  - slides.pdf
- - seminar-5-0-slides.pdf
  - seminar-5-1-trees-theory.ipynb
  - seminar-5-2-ensembling.ipynb
  - seminar-5-3-rf-tuning.ipynb
- - seminar-6-1-slides.pdf
  - seminar-6-2-pca.ipynb
- - seminar-7-1-slides.pdf
  - seminar-7-2-kmeans.ipynb
- - seminar-8-1-slides.pdf
  - seminar-8-2-perceptron.ipynb
  - seminar-8-3-perceptron-practice.ipynb
  - seminar-8-4-intro-to_backprop.ipynb
- - seminar-9-1-slides.pdf
  - seminar-9-2-practice.ipynb
- - important_conversations.csv
  - seminar-1-1-NLP_intro.ipynb
  - seminar-1-2-contest-baseline.ipynb
- - seminar10-1-deepfakes_theory.ipynb
- - seminar11-1-pytorch.ipynb
- - seminar-2-1-embeddings.ipynb
  - seminar-2-2-tfidf.ipynb
- - checkpoint_100_epoch_500.hdf5
  - seminar-3-1-language-models.ipynb
  - seminar-3-2-char-rnn.ipynb
  - seminar-3-2.5-rnn-lstm-theory.ipynb
  - util.py
  - weights.hdf5
- - seminar-4-2-seq2seq-practice.ipynb
  - util.py
- - seminar5-1-semantic-segmentation.ipynb
  - seminar5-2-data-preproc.ipynb
  - seminar5-3-predict-buildings.ipynb
- - seminar6-1-rcnn-theory.ipynb
  - seminar6-2-rcnn-practice.ipynb
- - seminar7-1-lenet-alexnet-googlenet-vgg.ipynb
  - seminar7-2-resnet-inception-xception.ipynb
  - seminar7-3-squeeze-mobile-dense.ipynb
- - seminar8-1-texture_synthesis.ipynb
  - seminar8-2-vanilla-style-transfer.ipynb
- - lfw_dataset.py
  - seminar9-1-simple_autoencoders.ipynb
  - seminar9-2-variational-autoencoder-theory.ipynb
  - seminar9-3-variational-autoencoder-practice.ipynb
- - seminar-1-nlp-intro.pdf
- - 2-word-embeddings-practice.ipynb
- - 3-text-classification.ipynb
- - 4-rnn-language-models.ipynb
  - names
- - seminar5-1-semantic-segmentation.ipynb
  - seminar5-2-data-preproc.ipynb
  - seminar5-3-predict-buildings.ipynb
- - seminar6-2-rcnn-practice.ipynb
- - seminar7-1-lenet-alexnet-googlenet-vgg.ipynb
  - seminar7-2-resnet-inception-xception.ipynb
  - seminar7-3-mobile-dense-resnext.ipynb
  - seminar7-4-squeeze [optional].ipynb
  - seminar7-5-batch_norm-train_tricks.ipynb
- - lfw_dataset.py
  - seminar8-1-simple-autoencoders.ipynb
  - seminar8-2-variational-autoencoder-theory.ipynb
  - seminar8-3-variational-autoencoder-practice.ipynb
- - seminar9-1-texture_synthesis.ipynb
  - seminar9-2-vanilla-style-transfer.ipynb
  - seminar9-3-fast-style-transfer.ipynb
- - seminar-1-nlp-intro.pdf
- - cs231n_2019_lecture02.pdf
  - cs231n_2019_lecture03.pdf
  - numpy_tutorial.ipynb
- - cs231n_2019_lecture04.pdf
  - cs231n_2019_lecture05.pdf
- - cs231n_2019_lecture07.pdf
  - cs231n_2019_lecture08.pdf
- - workshop-1-1-python.ipynb
  - workshop-1-2-YOLO-colab.ipynb
- - workshop-2-1-SoundRecognition.ipynb
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