stober

#! /usr/bin/env python
"""
Author: Jeremy M. Stober
Program: SOFTMAX.PY
Date: Wednesday, February 29 2012
Description: Simple softmax function.
"""

import numpy as np
npa = np.array

grenade

#!/bin/bash

mkdir -p ~/.ssh

# generate new personal ed25519 ssh keys
ssh-keygen -o -a 100 -t ed25519 -f ~/.ssh/id_ed25519 -C "rob thijssen <[email protected]>"
ssh-keygen -o -a 100 -t ed25519 -f ~/.ssh/id_robtn -C "rob thijssen <[email protected]>"

# generate new host cert authority (host_ca) ed25519 ssh key
# used for signing host keys and creating host certs

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)

kukuruza

from math import sqrt

def put_kernels_on_grid (kernel, pad = 1):

  '''Visualize conv. filters as an image (mostly for the 1st layer).
  Arranges filters into a grid, with some paddings between adjacent filters.

  Args:
    kernel:            tensor of shape [Y, X, NumChannels, NumKernels]
    pad:               number of black pixels around each filter (between them)

tomokishii

#
#  mnist_cnn_bn.py   date. 5/21/2016
#                    date. 6/2/2017 check TF 1.1 compatibility
#

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

import os

shagunsodhani

GloVe: Global Vectors for Word Representation

Introduction

• Introduces a new global log-bilinear regression model which combines the benefits of both global matrix factorization and local context window methods.

Global Matrix Factorization Methods

• Decompose large matrices into low-rank approximations.

kylehounslow

from __future__ import print_function
import requests
import json
import cv2

addr = 'http://localhost:5000'
test_url = addr + '/api/test'

# prepare headers for http request
content_type = 'image/jpeg'

nikitametha

This is a guide on how to install Caffe for Ubuntu 16.04 and above, without GPU support (No CUDA required).

Prerequisites:

OpenCV

sudo apt-get install libopencv-dev python-opencv

OpenBLAS OR Atlas

aneesh-joshi

import tensorflow as tf
import numpy as np

corpus_raw = 'He is the king . The king is royal . She is the royal  queen '

# convert to lower case
corpus_raw = corpus_raw.lower()

words = []
for word in corpus_raw.split():

Geoyi

How to install virtualenv:

Install pip first

sudo apt-get install python3-pip

Then install virtualenv using pip3

sudo pip3 install virtualenv