Browser links

30/3/2021

  • https://learning.edx.org/course/course-v1:TUMx+AWMEx+3T2020/home

  • https://elearning.tableau.com/

  • https://github.com/niais/mv-ignet
  • https://github.com/ekazakos/temporal-binding-network
  • https://github.com/Showmax/kinetics-downloader
  • https://colab.research.google.com/drive/1ViOfBaALFm1D5nI2Mwf4fSCzEC0d2oCR#scrollTo=sxsdBqhv5eMw
  • https://towardsdatascience.com/downloading-the-kinetics-dataset-for-human-action-recognition-in-deep-learning-500c3d50f776
  • https://www.youtube.com/watch?v=–3ouPhoy2A [Spaghetti]
  • https://yt1s.com/en3 [youtube downloader]
  • https://github.com/eriklindernoren/Action-Recognition
  • https://colab.research.google.com/drive/1tX3ldpW2pn0jPRlc8PCwV6XaSmMgcphP#scrollTo=0vII6vltr2NE

  • https://course19.fast.ai/videos/?lesson=2

  • https://towardsdatascience.com/the-simplest-way-of-making-gifs-and-math-videos-with-python-aec41da74c6e
  • https://towardsdatascience.com/estimating-optimal-learning-rate-for-a-deep-neural-network-ce32f2556ce0
  • https://setosa.io/ev/image-kernels/
  • Action recognition LRCN pre-processing

Audio

  • https://colab.research.google.com/drive/1hjRpzgv6IF9Eqa0LCrhF_FXMQfYmt8ME#scrollTo=1ub_b_L0uKOG
  • https://clear.ml/blog/audio-classification-with-pytorchs-ecosystem-tools/
  • https://clear.ml/blog/audio-classification-with-pytorchs-ecosystem-tools/
  • https://pytorch.org/tutorials/beginner/audio_preprocessing_tutorial.html
  • https://pytorch.org/tutorials/beginner/audio_preprocessing_tutorial.html
  • https://pytorch.org/tutorials/beginner/audio_preprocessing_tutorial.html
  • https://colab.research.google.com/github/pytorch/tutorials/blob/gh-pages/_downloads/7303ce3181f4dbc9a50bc1ed5bb3218f/audio_preprocessing_tutorial.ipynb#scrollTo=VE2fiv9MuuTi
  • https://link.springer.com/article/10.1007/s11042-017-5539-3
  • https://learnopencv.com/multi-label-image-classification-with-pytorch/
  • https://www.pluralsight.com/guides/image-classification-with-pytorch
  • open review
  • Resnets and variants

Fastai

  • https://colab.research.google.com/github/fastai/course-v3/blob/master/nbs/dl1/lesson1-pets.ipynb#scrollTo=Ot9bkhsTEaHy
  • https://forums.fast.ai/t/dense-vs-convolutional-vs-fully-connected-layers/191/3
  • https://www.fast.ai/2019/09/24/metrics/
  • https://github.com/fastai/fastbook
  • https://github.com/fastai/nbdev_template
  • https://nbdev.fast.ai/tutorial.html
  • https://forums.fast.ai/t/getting-started-with-fastai-v2/53927
  • pytorch tutorial

deeplizard

MMAction

  • https://mmaction2.readthedocs.io/en/latest/install.html#requirements
  • https://mmaction2.readthedocs.io/en/latest/recognition_models.html

job channels

  • https://wadsih.org.au/education-training-careers/data-science-jobs/

jupyter

  • http://localhost:8889/notebooks/har/audio/ucf101-audio.ipynb
  • http://localhost:8889/notebooks/har/nw-ucla/nw-ucla-rgb/tensorboard.ipynb
  • tensorboard
  • [tensorboard tutorial]neptune.ai/blog/tensorboard-tutorial)
  • Ml experiment tracking
  • http://localhost:8889/notebooks/har/nw-ucla/erik%20ucf101.ipynb
  • http://localhost:8889/notebooks/har/nw-ucla/nw-ucla-rgb/NW-UCLA-RGB-pytorch.ipynb#
  • http://localhost:8889/notebooks/har/nw-ucla/nw-ucla-rgb/PyTorch%20Tutorial.ipynb#
  • Visualization

Azure

  • [Azure Data Scientist Associate DP-100] (https://docs.microsoft.com/en-us/learn/certifications/azure-data-scientist/)
  • [Azure AI Engineer Associate AI-102] (https://docs.microsoft.com/en-us/learn/certifications/azure-ai-engineer/)

Oxfordmlschool

  • https://www.oxfordml.school/