boyangzhao

def EM_Gaussian(mu_init, sd_init, pi_init, n_iter=1000):
    # EM for Gaussian mixture models
    mu = mu_init
    sd = sd_init
    pi = pi_init
    K = len(pi_init) # number of Gaussians

    for n in range(n_iter):
        # Expectation step
        # calculate responsibilities for each Guassian

louislung

This gist is the implementation of RankNet using Keras Functional Api

For details please check this blog post.

keywords: learning to rank | tensorflow | keras | custom training loop | ranknet | lambdaRank

maximlt

@echo OFF
rem How to run a Python script in a given conda environment from a batch file.

rem It doesn't require:
rem - conda to be in the PATH
rem - cmd.exe to be initialized with conda init

rem Define here the path to your conda installation
set CONDAPATH=C:\ProgramData\Miniconda3
rem Define here the name of the environment

matteyeux

#!/bin/bash
#######################################################################
#
#  Project......: install_libimobiledevice.sh
#  Creator......: Dev-Jam remasterized by matteyeux on 27/12/15
#######################################################################

echo -e "\033[31mDev-Jam 12/01/2015 - Script to build & install Libimobiledevice\033[0m"
echo -e "\033[32m\033[1m\033[4m\033[5m\033[7mCreated by Dev-Jam, improved by @matteyeux on 27/12/15\033[0m"

d3rezz

# Finetune a tensorflow slim model (Resnet v1 50) on the flowers dataset in TFRecord format
# TFRecord files created using the script from https://github.com/kwotsin/create_tfrecords
# Trainining done in a Keras like way, where training and validation accuracy are computed every epoch
# Download resnet checkpoint from: http://download.tensorflow.org/models/resnet_v1_50_2016_08_28.tar.gz

import tensorflow as tf
import numpy as np
import os
import glob
from tqdm import tqdm

bhavika

import argparse
import os
import shutil
import time

import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim

lyonanderson

Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties config-number
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties serial-number
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties mlb-serial-number
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties IOPlatformSerialNumber
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties IOPlatformUUID
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties BootSessionUUID
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties SleepWakeUUID
Sep 28 22:49:11 iPhone-6S-Plus kernel[0] <Notice>: Sandbox: IOKitBrowser(1306) deny(1) iokit-get-properties IOCPUID
Sep 28 22:49:11 iPhone-6S-Plus kernel[

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)

felHR85

public class UsbData
{
	private String vendorId;
	private String vendorName;
	private String productId;
	private String productName;
	
	
	public UsbData(String vendorId, String vendorName, String productId, String productName)
	{

jvranish

/* compile with:
on linux:   gcc -g stack_traces.c
on OS X:    gcc -g -fno-pie stack_traces.c
on windows: gcc -g stack_traces.c -limagehlp
*/

#include <signal.h>
#include <stdio.h>
#include <assert.h>