Jud

/*****************************************************************************
 *                QuantCup 1:   Price-Time Matching Engine
 *
 * Submitted by: voyager
 * 
 * Design Overview:
 *   In this implementation, the limit order book is represented using 
 *   a flat linear array (pricePoints), indexed by the numeric price value. 
 *   Each entry in this array corresponds to a specific price point and holds 
 *   an instance of struct pricePoint. This data structure maintains a list 

1wErt3r

;SMBDIS.ASM - A COMPREHENSIVE SUPER MARIO BROS. DISASSEMBLY
;by doppelganger ([email protected])

;This file is provided for your own use as-is.  It will require the character rom data
;and an iNES file header to get it to work.

;There are so many people I have to thank for this, that taking all the credit for
;myself would be an unforgivable act of arrogance. Without their help this would
;probably not be possible.  So I thank all the peeps in the nesdev scene whose insight into
;the 6502 and the NES helped me learn how it works (you guys know who you are, there's no 

walkie

% MIPS Assembly language definition for the LaTeX `listings' package
%
% The list of instructions and directives are those understood by the
% MARS MIPS Simulator [http://courses.missouristate.edu/KenVollmar/MARS/]
%
% Author: Eric Walkingshaw <[email protected]>
%
% This code is in the public domain.
%
% Here is an example style. I like it for slides, but you might want 

jamiees2

# Enter your code here. Read input from STDIN. Print output to STDOUT
class Node:
    def __init__(self,value,point):
        self.value = value
        self.point = point
        self.parent = None
        self.H = 0
        self.G = 0
    def move_cost(self,other):
        return 0 if self.value == '.' else 1

niw

/*
 * A simple libpng example program
 * http://zarb.org/~gc/html/libpng.html
 *
 * Modified by Yoshimasa Niwa to make it much simpler
 * and support all defined color_type.
 *
 * To build, use the next instruction on OS X.
 * $ brew install libpng
 * $ clang -lz -lpng16 libpng_test.c

craffel

import matplotlib.pyplot as plt

def draw_neural_net(ax, left, right, bottom, top, layer_sizes):
    '''
    Draw a neural network cartoon using matplotilb.
    
    :usage:
        >>> fig = plt.figure(figsize=(12, 12))
        >>> draw_neural_net(fig.gca(), .1, .9, .1, .9, [4, 7, 2])
    

PurpleBooth

Project Title

One Paragraph of project description goes here

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.

Prerequisites

ygotthilf

ssh-keygen -t rsa -b 4096 -m PEM -f jwtRS256.key
# Don't add passphrase
openssl rsa -in jwtRS256.key -pubout -outform PEM -out jwtRS256.key.pub
cat jwtRS256.key
cat jwtRS256.key.pub

wangruohui

In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.

Table of Contents

• Install NVIDIA Graphics Driver via apt-get
• Install NVIDIA Graphics Driver via runfile
  • Remove Previous Installations (Important)
  • Download the Driver
  • Install Dependencies
  • Creat Blacklist for Nouveau Driver

• Stop lightdm/gdm/kdm

wassname

"""
A weighted version of categorical_crossentropy for keras (2.0.6). This lets you apply a weight to unbalanced classes.
@url: https://gist.github.com/wassname/ce364fddfc8a025bfab4348cf5de852d
@author: wassname
"""
from keras import backend as K
def weighted_categorical_crossentropy(weights):
    """
    A weighted version of keras.objectives.categorical_crossentropy