Smoothies
- Frozen Berries
- Thickened Cream
Vegetables
- Any frozen variety (check carbs)
Eggs (Any)
// Updated: Aug. 20, 2024 | |
// Run: node testRegex.js whatever.txt | |
// Live demo: https://jina.ai/tokenizer | |
// LICENSE: Apache-2.0 (https://www.apache.org/licenses/LICENSE-2.0) | |
// COPYRIGHT: Jina AI | |
const fs = require('fs'); | |
const util = require('util'); | |
// Define variables for magic numbers | |
const MAX_HEADING_LENGTH = 7; |
Smoothies
Vegetables
Eggs (Any)
Code for Keras plays catch blog post
python qlearn.py
import tensorflow as tf | |
import numpy as np | |
import os | |
import zconfig | |
import utils | |
class RBM(object): |
category | value | sector | |
---|---|---|---|
UK production emissions | 632 | UK | |
Carbon flows from EU | 88 | EU | |
Carbon flows to EU | -61 | EU | |
Carbon flows from other Annex 1 | 82 | Annex 1 | |
Carbon flows to other Annex 1 | -39 | Annex 1 | |
Carbon flows from non-Annex 1 | 104 | Other non-Annex 1 | |
Carbon flows from non-Annex 1 | 64 | China | |
Carbon flows to non-Annex 1 | -25 | Non-Annex 1 | |
UK consumption emissions | 845 | UK |
# | |
# This Python script makes a summary of a football game by cutting | |
# the video around the 10 % loudest moments, which generally | |
# include the goals and other important events. | |
# For more details, see this blog post: | |
# http://zulko.github.io/blog/2014/07/04/automatic-soccer-highlights-compilations-with-python/ | |
# | |
# LICENCE: Creative Commons 0 - Public Domain | |
# I, the author of this script, wave any rights and place this work in the public domain. | |
# |
$script = <<SCRIPT | |
apt-get update --fix-missing | |
apt-get install -y python-software-properties | |
add-apt-repository ppa:terry.guo/gcc-arm-embedded | |
apt-get update | |
apt-get install -y build-essential | |
apt-get install -y gcc-arm-none-eabi | |
apt-get install -y dfu-util | |
apt-get install -y git-core |
A lot of these are outright stolen from Edward O'Campo-Gooding's list of questions. I really like his list.
I'm having some trouble paring this down to a manageable list of questions -- I realistically want to know all of these things before starting to work at a company, but it's a lot to ask all at once. My current game plan is to pick 6 before an interview and ask those.
I'd love comments and suggestions about any of these.
I've found questions like "do you have smart people? Can I learn a lot at your company?" to be basically totally useless -- everybody will say "yeah, definitely!" and it's hard to learn anything from them. So I'm trying to make all of these questions pretty concrete -- if a team doesn't have an issue tracker, they don't have an issue tracker.
I'm also mostly not asking about principles, but the way things are -- not "do you think code review is important?", but "Does all code get reviewed?".
import json | |
from pprint import pprint as pp | |
import numpy as np | |
from numba import autojit, typeof, int32 | |
INF = float('inf') | |
@autojit | |
def jenks_matrics_init(data, n_classes, ): |
import json | |
from pprint import pprint as pp | |
def jenks_matrices_init(data, n_classes): | |
#fill the matrices with data+1 arrays of n_classes 0s | |
lower_class_limits = [] | |
variance_combinations = [] | |
for i in xrange(0, len(data)+1): | |
temp1 = [] | |
temp2 = [] |