Computer vision topics

Задачи CV

https://docs.google.com/presentation/d/1k49VqEXLZjdh70N6Xjt7ytYQ82M5NBKtF7IJxzGrk3A/edit#slide=id.p
https://disk.yandex.ru/d/WZDlNAPIFrL-bQ/GMT20230904-131154_Recording_1920x1080.mp4

Классический ML

Кластеризация

KNN

https://cs231n.github.io/classification/#k---nearest-neighbor-classifier
https://docs.google.com/presentation/d/1HMUfWEAVLWreH7EYbztg4EI8WAq7CqJWqGUiG1YC27k/edit#slide=id.g985d87da51_0_84

K-means

https://colab.research.google.com/drive/1t8NsXxZW7tyCFizXoKW1HrnOjTxgxwe2#scrollTo=V3uQ1gNIvDof
https://education.yandex.ru/handbook/ml/article/klasterizaciya
https://scikit-learn.org/stable/modules/clustering.html

DB-Scan

https://colab.research.google.com/drive/1t8NsXxZW7tyCFizXoKW1HrnOjTxgxwe2#scrollTo=KTDxQN_GsCXj
https://scikit-learn.org/stable/modules/clustering.html#dbscan

Линейные модели

Loss-функция

https://colab.research.google.com/drive/1XA839GhGM9MOgqz6aKmFIlcAXB7f4c2K#scrollTo=495dFZT6oocy

Линейная регресиия.

https://colab.research.google.com/drive/1XA839GhGM9MOgqz6aKmFIlcAXB7f4c2K#scrollTo=2nRrlLeurEar

Логистическая регресиия

https://scikit-learn.org/stable/modules/linear_model.html#logistic-regression

градиентный спуск

https://colab.research.google.com/drive/1XA839GhGM9MOgqz6aKmFIlcAXB7f4c2K#scrollTo=cfokn1dJuD-G
https://cs231n.github.io/optimization-1/#gradcompute

регуляризация

https://colab.research.google.com/drive/1XA839GhGM9MOgqz6aKmFIlcAXB7f4c2K#scrollTo=WhUnTY-NuD_p
https://cs231n.github.io/neural-networks-2/#reg
https://docs.google.com/presentation/d/1HnXRCye2taclh6vvnxq3Wlc2X54HhsP0zPXQ-5WBidM/edit#slide=id.gfa0ed26e67_0_9

Линейный классификатор

https://colab.research.google.com/drive/1XA839GhGM9MOgqz6aKmFIlcAXB7f4c2K#scrollTo=0SutrO29uD_B
https://cs231n.github.io/linear-classify/#loss-function
https://docs.google.com/presentation/d/1HnXRCye2taclh6vvnxq3Wlc2X54HhsP0zPXQ-5WBidM/edit#slide=id.g60c6efa2cf_0_27

Метрики

https://github.com/Gan4x4/ml_snippets/blob/main/Metrics.ipynb
https://education.yandex.ru/handbook/ml/article/metriki-klassifikacii-i-regressii

bias-variance traid-off

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=wjlRni2G3OSi

сross-validation, стратификация

https://education.yandex.ru/handbook/ml/article/kross-validaciya
https://cs231n.github.io/classification/#validation-sets-for-hyperparameter-tuning

SVM

https://drive.google.com/file/d/1Vs2B5M_lmhyOEPhROi-s5O9wmy7qUpCf/view?usp=sharing
https://www.youtube.com/watch?v=_PwhiWxHK8o

Древесные модели

деревья решений

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=2My8Ah1C3OSB

random forest

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=dq7R5vgj3OTW

RSM,Bootstrap

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=NZ9MbGv33OTM

bagging

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=8oFZ3fnD3OTB
https://education.yandex.ru/handbook/ml/article/ansambli-v-mashinnom-obuchenii

Блендинг и Стэкинг

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=WOyAKG0l3OUS

boosting

https://colab.research.google.com/drive/1_uJnFmBHGV92hPlMdn_YbC4y9iPumVKF#scrollTo=ghkLR5GY3OTx
https://education.yandex.ru/handbook/ml/article/gradientnyj-busting
https://colab.research.google.com/drive/1hILdJzsuAsXabA4aIwtb9RGgUn_bvhCL

Подготовка данных

нормировка

https://cs231n.github.io/neural-networks-2/#datapre

балансировка данных

https://colab.research.google.com/drive/1t8NsXxZW7tyCFizXoKW1HrnOjTxgxwe2#scrollTo=SCI7vE1R5yJJ

Deep learning

Multi Layer perceptron(MLP)

https://colab.research.google.com/drive/1FIzS0gSlKag4u-lhRTG9F1DXgg7H68nx#scrollTo=vSdq109FpQOx
https://colab.research.google.com/github/bentrevett/pytorch-image-classification/blob/master/1_mlp.ipynb
https://colab.research.google.com/drive/1FIzS0gSlKag4u-lhRTG9F1DXgg7H68nx#scrollTo=vSdq109FpQOx

Backpropagation

https://colab.research.google.com/drive/1FIzS0gSlKag4u-lhRTG9F1DXgg7H68nx#scrollTo=PiD-BR1BpQNj
https://cs231n.github.io/optimization-2/
https://docs.google.com/presentation/d/1dWVUOYuWPVgcp5Vk29D7lacoboDJMHnOW2TMx2cNrig/edit#slide=id.p
https://disk.yandex.ru/d/WZDlNAPIFrL-bQ

Softmax & Losses

https://colab.research.google.com/drive/1XA839GhGM9MOgqz6aKmFIlcAXB7f4c2K#scrollTo=KBXbZTvHuD_2
https://cs231n.github.io/neural-networks-2/#losses

Optimizers

https://colab.research.google.com/drive/1dPPpysxdJqQBUo8pgUYcmujzCge0HpHI#scrollTo=5BCqDo5k7ZN0
https://cs231n.github.io/neural-networks-3/#update
https://docs.google.com/presentation/d/1h7XLXwO04L_pnqTGXG9lzkCDPqTkCNPFdyQDrCEve3w/edit

Dropout

https://colab.research.google.com/drive/1dPPpysxdJqQBUo8pgUYcmujzCge0HpHI#scrollTo=SHwT36C87ZNk
https://docs.google.com/presentation/d/1ZE21WSq7BOabn2Hz70_RugxCWUHUkirar5jhalqpZ8g/edit#slide=id.gb04cf3c473_0_34

Batch & Layer Norm

https://colab.research.google.com/drive/1dPPpysxdJqQBUo8pgUYcmujzCge0HpHI#scrollTo=wLRapArc7ZM_
https://cs231n.github.io/neural-networks-2/#batchnorm

Визуальные данные

CNN

Свертки

https://github.com/EPC-MSU/EduNet-lectures/blob/dev-2.0/out/L06_CNN.ipynb
https://cs231n.github.io/convolutional-networks/
https://docs.google.com/presentation/d/1THQa0ILp6UOJKkxlJ4U6iPDUhg9NMfd4wNg2iFmYia4/edit
https://www.youtube.com/watch?v=6w1mO90stc0&list=PL-KRBoUl__Zc5dYuItKv-64Wbfrq5tZkZ&index=2&t=5669s

Архитектуры

https://github.com/EPC-MSU/EduNet-lectures/blob/dev-2.0/out/L08_NN_architectures.ipynb
https://docs.google.com/presentation/d/1ArZq8AF1tSqUhiGlewEAwq3vy7sUsP1LaYbgTXc9cOE/edit
https://www.youtube.com/watch?v=6w1mO90stc0&list=PL-KRBoUl__Zc5dYuItKv-64Wbfrq5tZkZ&index=2&t=5669s

Global Average Pooling(GAP)

https://pytorch.org/docs/stable/generated/torch.nn.AdaptiveAvgPool2d.html
https://docs.google.com/presentation/d/1ArZq8AF1tSqUhiGlewEAwq3vy7sUsP1LaYbgTXc9cOE/edit#slide=id.gad00070d7c_0_16

TransferLearning

https://colab.research.google.com/drive/1pWb7tRbIDNGzazLKdCLCOEdRW3LW7uFv#scrollTo=jIjH8EOy05tA

OCR

https://github.com/tesseract-ocr/tesseract

Инструменты

CVAT

https://github.com/cvat-ai/cvat
https://www.cvat.ai/

WanDB

https://colab.research.google.com/github/wandb/examples/blob/master/colabs/intro/Intro_to_Weights_%26_Biases.ipynb
https://wandb.ai/site

Tensorboard

https://colab.research.google.com/drive/1257fyQw731FGE3dywS561_rIaBTGLfqB
https://pytorch.org/docs/stable/tensorboard.html
https://pytorch.org/tutorials/intermediate/tensorboard_tutorial.html

Визуализация

https://colab.research.google.com/drive/1Ii8mzZjbvnA_fsmNGkpCxwoZ8ID-78dk

Transformers(ViT)

Self-attention

https://docs.google.com/presentation/d/13czWy6xBBsbheYRIvUeb_1spABkEDnJp6g7u7gZhAzY/edit

ViT

https://colab.research.google.com/drive/1k8tEOTlVxsg9rK9Ey9a-ar_ZwGokYLGL

Metric Leaning

Embeddings

https://drive.google.com/file/d/1B6mSIVsPnYp_u3JirH57w7UdZKWY9nEg/view?usp=sharing
https://docs.google.com/presentation/d/1hkQWCthpHHALHxoa8KwVwAx71HrsLJwWbQwiwQu6PBY/edit

PML: ArcFace, TripletLoss

https://github.com/Gan4x4/ml_snippets/blob/main/Metric/Signs_sol_with_PML.ipynb
https://docs.google.com/presentation/d/1hkQWCthpHHALHxoa8KwVwAx71HrsLJwWbQwiwQu6PBY/edit#slide=id.g2a1a63d0de3_0_117

CLIP

https://colab.research.google.com/drive/1I6a0l7ZkRR_2ByDO_emBHMhFFD6dWg9-#scrollTo=S_Kwiba69deY

Autoencoders

https://colab.research.google.com/drive/1geGdh0JIP8Lkfk6-SSmrQLzMDuCxFijd
https://docs.google.com/presentation/d/1zza_CdOaajkd4h8QMY0nLOy8yQOYSIjXphQ16OQVAWU/edit#slide=id.p

Hard example Mining (HEM)

https://kevinmusgrave.github.io/pytorch-metric-learning/miners/#batchhardminer
https://docs.google.com/presentation/d/1hkQWCthpHHALHxoa8KwVwAx71HrsLJwWbQwiwQu6PBY/edit#slide=id.g2a1a63d0de3_0_124

ANN

HSNW

https://www.pinecone.io/learn/series/faiss/hnsw/

FAISS

https://www.pinecone.io/learn/series/faiss/faiss-tutorial/

LHS

https://www.pinecone.io/learn/series/faiss/locality-sensitive-hashing/

Segmentation

Задача сегментации

https://github.com/EPC-MSU/EduNet-lectures/blob/dev-2.0/out/L11_Segmentation_Detection.ipynb
https://docs.google.com/presentation/d/1Jh4oYLJ4-b_4cCTGeX_f8mgl-b-sQ2ujk2MslRjiJo4/edit
https://www.youtube.com/watch?v=Py9alzALD2k&list=PL-KRBoUl__Zc5dYuItKv-64Wbfrq5tZkZ&index=3

Метрики

IoU & Dice

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=A2DCjgn-9N1b

mAP

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=sIVYHyF09N23

Модели

SMP

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=HN0D6Rjb9N1_
https://github.com/qubvel/segmentation_models.pytorch#architectures-

Unet, FCN

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=5FxSRTXF9N17

DeepLab

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=JE8PMjFD9N19
https://docs.google.com/presentation/d/1Jh4oYLJ4-b_4cCTGeX_f8mgl-b-sQ2ujk2MslRjiJo4/edit

SWIN

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=DmSJSUkU9N2W

SAM

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=O3fBmyfL9N2q

Detection

YOLO

Версии YOLO

https://colab.research.google.com/drive/1GWizPqYAZcYEn3yTvTSJsTzLBhVKjjza

формат разметки YOLO

https://docs.ultralytics.com/ru/datasets/detect/#ultralytics-yolo-format

Multi-head networks

https://stackoverflow.com/questions/56004483/what-is-a-multi-headed-model-and-what-exactly-is-a-head-in-a-model

R-CNN

https://colab.research.google.com/drive/1GWizPqYAZcYEn3yTvTSJsTzLBhVKjjza

DETR

https://huggingface.co/docs/transformers/en/model_doc/detr

OWL-ViT

https://colab.research.google.com/drive/1YsQsXifAgixBW6jALbvBSio4coGPHUXm#scrollTo=MrX4SMpH9N2l

Depth estimation

Data updated: 2026-04-17 08:13 UTC