by Glenn Matlin / glennmatlin on all socials
- Download and copy all files in this gist to ~/.claude/
- Move the .pyfiles to~/.claude/hooks
- Restart Claude Code.
| Map | Action | 
|---|---|
| <F1> | Causes Netrw to issue help | 
| <cr> | Netrw will enter the directory or read the file | 
| <del> | Netrw will attempt to remove the file/directory | 
| - | Makes Netrw go up one directory | 
| a | Toggles between normal display, hiding (suppress display of files matching g:netrw_list_hide) showing (display only files which match g:netrw_list_hide) | 
| c | Make browsing directory the current directory | 
| C | Setting the editing window | 
| d | Make a directory | 
| # Ask for the user password | |
| # Script only works if sudo caches the password for a few minutes | |
| sudo true | |
| # Install kernel extra's to enable docker aufs support | |
| # sudo apt-get -y install linux-image-extra-$(uname -r) | |
| # Add Docker PPA and install latest version | |
| # sudo apt-key adv --keyserver hkp://keyserver.ubuntu.com:80 --recv-keys 36A1D7869245C8950F966E92D8576A8BA88D21E9 | |
| # sudo sh -c "echo deb https://get.docker.io/ubuntu docker main > /etc/apt/sources.list.d/docker.list" | 
| #!/usr/bin/env bash | |
| #Code adapted from https://gist.github.com/yangj1e/3641843c758201ebbc6c (Modified to Python3.5) | |
| cd ~ | |
| #wget https://3230d63b5fc54e62148e-c95ac804525aac4b6dba79b00b39d1d3.ssl.cf1.rackcdn.com/Anaconda2-2.4.0-Linux-x86_64.sh | |
| wget https://3230d63b5fc54e62148e-c95ac804525aac4b6dba79b00b39d1d3.ssl.cf1.rackcdn.com/Anaconda3-2.4.1-Linux-x86_64.sh | |
| bash Anaconda3-2.4.1-Linux-x86_64.sh -b | |
| echo 'PATH="/home/ubuntu/anaconda3/bin:$PATH"' >> .bashrc | |
| . .bashrc | 
##VGG16 model for Keras
This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
##VGG19 model for Keras
This is the Keras model of the 19-layer network used by the VGG team in the ILSVRC-2014 competition.
It has been obtained by directly converting the Caffe model provived by the authors.
Details about the network architecture can be found in the following arXiv paper:
Very Deep Convolutional Networks for Large-Scale Image Recognition
K. Simonyan, A. Zisserman
| """Kernel K-means""" | |
| # Author: Mathieu Blondel <[email protected]> | |
| # License: BSD 3 clause | |
| import numpy as np | |
| from sklearn.base import BaseEstimator, ClusterMixin | |
| from sklearn.metrics.pairwise import pairwise_kernels | |
| from sklearn.utils import check_random_state | 
| # script stolen from http://goo.gl/YbQyAQ | |
| # install.packages("tm") | |
| # install.packages("ggplot2") | |
| # install.packages("lsa") | |
| # install.packages("scatterplot3d") | |
| #install.packages("SnowballC") | |
| #if !(require('SnowballC')) then install.packages("SnowballC") | |
| library(tm) | |
| library(ggplot2) |