Intersting links about deep learning
Dec 3, 2020··
1 min read
Georg Heiler
general
- http://jalammar.github.io/
- https://lilianweng.github.io/lil-log/
- http://colah.github.io/posts/2014-03-NN-Manifolds-Topology/
- fast.ai updated for 2020 an V2
- fastai book
- dive into deep learning
- Yes you should understand backprop
- CS 329S: Machine Learning Systems Design
critique
- Vincent Warmerdam: The profession of solving (the wrong problem) | PyData Amsterdam 2019
- A Recipe for Training Neural Networks
generic ML useful tools
constraints
graph neural networks
- https://medium.com/dair-ai/an-illustrated-guide-to-graph-neural-networks-d5564a551783
- [node classification with pytorch geometric] (https://colab.research.google.com/drive/14OvFnAXggxB8vM4e8vSURUp1TaKnovzX?usp=sharing#scrollTo=dszt2RUHE7lW)
frameworks
graphs
time-series
- sktime and sktime-dl
- pytorch-forecasting
- A Multivariate Deep Learning for Time Series Forecasting Library
- tsai state of the art sequence modeling
- GluonTS - Probabilistic Time Series Modeling in Python
- Awesome python time-series tooling not so much neural networks. But still very useful feature generators.
- ROCKET transforms time series using random convolutional kernels
- Orion - multivariate time-series anomaly detection
- How to prepare Time Series Data for LSTM Networks
- neural prophet
Varous time-series handling approaches:
- transformer https://www.youtube.com/watch?v=GiD87DeadYY
- 1D CNN, convert to images, convert to text https://www.youtube.com/watch?v=WoLlZLdoEQk
- Attention & time-series review https://towardsdatascience.com/attention-for-time-series-classification-and-forecasting-261723e0006d
- transformer:
- classificaton:
self supervised learing
anomaly detection
- Deep Few-shot Anomaly Detection https://towardsdatascience.com/deep-few-shot-anomaly-detection-b33f130d1f80