mblondel

# Mathieu Blondel, September 2010
# License: BSD 3 clause

import numpy as np
from numpy import linalg
import cvxopt
import cvxopt.solvers

def linear_kernel(x1, x2):
    return np.dot(x1, x2)

thorikawa

#include <opencv2/opencv.hpp>
#include <opencv2/nonfree/nonfree.hpp>
#include <iostream>
#include <vector>
#include <cmath>

using namespace std;
using namespace cv;

const double THRESHOLD = 400;

tristanwietsma

from __future__ import division
from numpy import *

class AdaBoost:

    def __init__(self, training_set):
        self.training_set = training_set
        self.N = len(self.training_set)
        self.weights = ones(self.N)/self.N
        self.RULES = []

jcraane

<?xml version="1.0" encoding="UTF-8"?>
<configuration scan="true">
    <appender name="consoleAppender" class="ch.qos.logback.core.ConsoleAppender">
        <encoder>
            <charset>UTF-8</charset>
            <Pattern>%d %-4relative [%thread] %-5level %logger{35} - %msg%n</Pattern>
        </encoder>
    </appender>

    <appender name="FILE" class="ch.qos.logback.core.rolling.RollingFileAppender">

xjia1

\documentclass{book}
\usepackage{amsmath}
\usepackage{fontspec}
\usepackage{xunicode}
\usepackage{indentfirst}

%% XeTeX adds code when switching latin (0) or boundary (255) to CJK (1, 2, 3)
\XeTeXinterchartokenstate = 1

%% Fonts for Latin and CJK

gwtaylor

""" Python implementation of the OASIS algorithm.
Graham Taylor

Based on Matlab implementation of:
Chechik, Gal, et al.
"Large scale online learning of image similarity through ranking."
The Journal of Machine Learning Research 11 (2010): 1109-1135.
"""

from __future__ import division

bearpaw

Caffe + Ubuntu 12.04 64bit + CUDA 6.5 配置说明

本步骤能实现用Intel核芯显卡来进行显示， 用NVIDIA GPU进行计算。

1. 安装开发所需的依赖包

安装开发所需要的一些基本包

sudo apt-get install build-essential
sudo apt-get install vim cmake git
sudo apt-get install libprotobuf-dev libleveldb-dev libsnappy-dev libopencv-dev libboost-all-dev libhdf5-serial-dev

dynamicguy

# install dependencies
sudo apt-get update
sudo apt-get install -y build-essential
sudo apt-get install -y cmake
sudo apt-get install -y libgtk2.0-dev
sudo apt-get install -y pkg-config
sudo apt-get install -y python-numpy python-dev
sudo apt-get install -y libavcodec-dev libavformat-dev libswscale-dev
sudo apt-get install -y libjpeg-dev libpng-dev libtiff-dev libjasper-dev
 

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

kylemcdonald

Theory of Building Caffe on OS X

Introduction

Our goal is to run python -c "import caffe" without crashing. For anyone who doesn't spend most of their time with build systems, getting to this point can be extremely difficult on OS X. Instead of providing a list of steps to follow, I'll try to explain why each step happens.

This page has OS X specific install instructions.

I assume: