hpc-ml
my notes on ML/DL and HPC.
Running environment (JupyterHub at OLCF)
- First login (http://jupyter.olcf.ornl.gov), and launch a terminal:
# create a spec based on current BASE conda environment
conda list --explicit > spec-file.txt
# create a new environment, which will persist
conda create -p /ccs/proj/gen150/fwang2/mistral --file spec-file.txt
# other customization if needed, then activate
source activate /ccs/proj/gen150/fwang2/mistral
- Make newly created environment visiable
python -m ipykernel install --user --name mistral --display-name mistral
Now, when you start a new launcher, you should see the new kernel “mistral” listed.
Regression
Dimension Reduction
Clustering
Deep Learning
- Gradient Descent
- Compute Graph, Back Propagation
- Neural Network Concept
- 2-Layer Gradient Descent
- 3-Layer Gradient Descent
- Regularization and dropout
- Activation Functions
- CNN
- RNN and LSTM
- Transferred Learning
- Federated Learning
Scalable Learning
RNN and LSTM
- My RNN Notes
- Unreasonable effectiveness of RNN
- Understanding LSTM, Colah’s Blog, there is accompanying Krish’s explaination.
- Word embedding
- Running Jupyter on Summit