by Glenn Matlin / glennmatlin
on all socials
- Download and copy all files in this gist to
~/.claude/
- Move the
.py
files 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) |