stanlee321

-------------------------------------------------------
CBEffects Parameter Documentation
-------------------------------------------------------

This is the overwhelmingly large .txt file containing all of the parameters you can possibly put in a Data Table for CBEffects.

Includes parameters for CBEffects One, One and One-Fourth, One and One-Half, One and Three-Fourths, One and Four-Fifths, Two, Two and One-Fourth, Two and Two-Fifths, Two and Four-Ninths.

--------------------------------------------------------
--------------------------------------------------------

stanlee321

function [J grad] = nnCostFunction(nn_params, ...
                                   input_layer_size, ...
                                   hidden_layer_size, ...
                                   num_labels, ...
                                   X, y, lambda)
%NNCOSTFUNCTION Implements the neural network cost function for a two layer
%neural network which performs classification
%   [J grad] = NNCOSTFUNCTON(nn_params, hidden_layer_size, num_labels, ...
%   X, y, lambda) computes the cost and gradient of the neural network. The
%   parameters for the neural network are "unrolled" into the vector

stanlee321

from numpy.fft import fft, ifft, fft2, ifft2, fftshift
import numpy as np

def fft_convolve2d(x,y):
    """ 2D convolution, using FFT"""
    fr = fft2(x)
    fr2 = fft2(np.flipud(np.fliplr(y)))
    m,n = fr.shape
    cc = np.real(ifft2(fr*fr2))
    cc = np.roll(cc, -m/2+1,axis=0)

stanlee321

stanlee321

# Copyright (C) 2016 Martina Pugliese

from boto3 import resource
from boto3.dynamodb.conditions import Key

# The boto3 dynamoDB resource
dynamodb_resource = resource('dynamodb')


def get_table_metadata(table_name):

stanlee321

#!/bin/bash
v4l2-ctl -c brightness=0
v4l2-ctl -c contrast=120
v4l2-ctl -c white_balance_temperature_auto=0
v4l2-ctl -c gamma=120
v4l2-ctl -c white_balance_temperature=4700
v4l2-ctl -c sharpness=100
v4l2-ctl -c backlight_compensation=0
v4l2-ctl -c focus_absolute=10
v4l2-ctl --list-ctrls-menus

stanlee321

import boto3

class tableCreate(object):
    def __init__(self, **kwargs):
        self.__dict__.update(kwargs)

    # Query client and list_tables to see if table exists or not
    def queryCreate(self):
        # Instantiate your dynamo client object
        client = boto3.client('dynamodb')

stanlee321

From time to time, Musk will send out an e-mail to the entire company to enforce a new policy or let them know about something that's bothering him. One of the more famous e-mails arrived in May 2010 with the subject line: Acronyms Seriously Suck:

There is a creeping tendency to use made up acronyms at SpaceX. Excessive use of made up acronyms is a significant impediment to communication and keeping communication good as we grow is incredibly important. Individually, a few acronyms here and there may not seem so bad, but if a thousand people are making these up, over time the result will be a huge glossary that we have to issue to new employees. No one can actually remember all these acronyms and people don't want to seem dumb in a meeting, so they just sit there in ignorance. This is particularly tough on new employees.

That needs to stop immediately or I will take drastic action - I have given enough warning over the years. Unless an acronym is approved by me, it should not enter the SpaceX glossary.

stanlee321

# John Horton
# www.john-joseph-horton.com

# Description: Answer to Quora question about machine learning hourly rates
# "http://www.quora.com/Machine-Learning/What-do-contractors-in-machine-learning-charge-by-the-hour"

from BeautifulSoup import BeautifulSoup
import urllib2 

def contractors(skill, offset):

stanlee321

sudo apt install libatlas-base-dev protobuf-compiler python-pil python-lxml python-tk
pip3 install tensorflow