... or Why Pipelining Is Not That Easy
Golang Concurrency Patterns for brave and smart.
By @kachayev
| model = xgb.Booster(model_file='your.model') | |
| model.feature_names = xgtrain.feature_names # Note: xgtrain is your train file with features. | |
| model.feature_types = xgtrain.feature_types | |
| # Number of trees in the model | |
| num_trees = len(model.get_dump()) | |
| # dump all of the trees to tree folder | |
| for tree_index in range(num_trees): | |
| dot = xgb.to_graphviz(model, num_trees=tree_index) |
| --- | |
| ### | |
| # Elasticsearch Rolling restart using Ansible | |
| ### | |
| ## | |
| ## Why is this needed? | |
| ## | |
| # | |
| # Even if you use a serial setting to limit the number of nodes processed at one |
... or Why Pipelining Is Not That Easy
Golang Concurrency Patterns for brave and smart.
By @kachayev
| import numpy as np | |
| from matplotlib import pylab as plt | |
| #from mpltools import style # uncomment for prettier plots | |
| #style.use(['ggplot']) | |
| ''' | |
| function definitions | |
| ''' | |
| # generate all bernoulli rewards ahead of time | |
| def generate_bernoulli_bandit_data(num_samples,K): |
GNU Octave is a high-level interpreted language, primarily intended for numerical computations.
(via GNU Octave)
Hint: I also mad an octave docset for Dash: https://github.com/obstschale/octave-docset
| <% flash.each do |type, message| %> | |
| <div class="alert <%= bootstrap_class_for(type) %> fade in"> | |
| <button class="close" data-dismiss="alert">×</button> | |
| <%= message %> | |
| </div> | |
| <% end %> |
This post is based on my blog post: http://blog.xdite.net/posts/2012/07/09/3-way-to-speedup-asset-pipeline/
Here are my three tips for speedup asset pipeline precompile process:
cribbed from http://pastebin.com/xgzeAmBn
Templates to remind you of the options and formatting for the different types of objects you might want to document using YARD.