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@kylemcdonald
kylemcdonald / pytorch_setup.sh
Created August 29, 2018 02:48
Install CUDA 9.2, cuDNN 7.2.1, Anaconda and PyTorch on Ubuntu 16.04.
View pytorch_setup.sh
# tested on AWS p2.xlarge August 29, 2018
# install CUDA
sudo apt-get update && sudo apt-get install wget -y --no-install-recommends
CUDA_URL="https://developer.nvidia.com/compute/cuda/9.2/Prod2/local_installers/cuda-repo-ubuntu1604-9-2-local_9.2.148-1_amd64"
wget -c ${CUDA_URL} -O cuda.deb
sudo dpkg --install cuda.deb
sudo apt-key add /var/cuda-repo-9-2-local/7fa2af80.pub
sudo apt-get update
sudo apt-get install -y cuda
@iandees
iandees / dlib_plus_osm.md
Last active May 30, 2018 19:07
Detecting Road Signs in Mapillary Images with dlib C++
View dlib_plus_osm.md

image

I've been interested in computer vision for a long time, but I haven't had any free time to make any progress until this holiday season. Over Christmas and the New Years I experimented with various methodologies in OpenCV to detect road signs and other objects of interest to OpenStreetMap. After some failed experiments with thresholding and feature detection, the excellent /r/computervision suggested using the dlib C++ module because it has more consistently-good documentation and the pre-built tools are faster.

After a day or two figuring out how to compile the examples, I finally made some progress:

Compiling dlib C++ on a Mac with Homebrew

  1. Clone dlib from Github to your local machine:
@syhw
syhw / dnn_compare_optims.py
Created July 21, 2014 09:07
comparing SGD vs SAG vs Adadelta vs Adagrad
View dnn_compare_optims.py
"""
A deep neural network with or w/o dropout in one file.
"""
import numpy
import theano
import sys
import math
from theano import tensor as T
from theano import shared
@goldingn
goldingn / CUR4FIC
Last active January 3, 2016 05:49
Playing with CUR decomposition (versus k-means) as a method for picking inducing points in sparse Gaussian processes
View CUR4FIC
# clear the workspace
rm(list = ls())
# load the relevant libraries
# install.packages(rCUR)
library(rCUR) # for CUR decomposition
# install.packages(irlba)
library(irlba) # for fast svd
@GaelVaroquaux
GaelVaroquaux / bench_dbscan.py
Last active December 20, 2015 10:19
Benchmarking scikit_learn 0.14.X release
View bench_dbscan.py
import numpy as np
import time
from sklearn import cluster
from sklearn import datasets
lfw = datasets.fetch_lfw_people()
X_lfw = lfw.data[:, :5]
eps = 8. # This choice of EPS gives 44 clusters
@spaghetti-source
spaghetti-source / readmnist.cc
Created May 21, 2013 14:35
Read MNIST Database (handwritten digits)
View readmnist.cc
// Read MNIST Database (handwritten digits)
//
// Usage:
// 1. download
// train-images-idx3-ubyte.gz
// train-labels-idx2-ubyte.gz
// from
// http://yann.lecun.com/exdb/mnist/
// and extract them.
//
@iamatypeofwalrus
iamatypeofwalrus / roll_ipython_in_aws.md
Last active February 22, 2022 22:25
Create an iPython HTML Notebook on Amazon's AWS Free Tier from scratch.
View roll_ipython_in_aws.md

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

  • An active AWS account. First time sign-ups are eligible for the free tier for a year
  • One Micro Tier EC2 Instance
  • With AWS we will use the stock Ubuntu Server AMI and customize it.
  • Anaconda for Python.
  • Coffee/Beer/Time
@larsmans
larsmans / kmeans.py
Created February 14, 2013 13:38
k-means clustering in pure Python
View kmeans.py
#!/usr/bin/python
#
# K-means clustering using Lloyd's algorithm in pure Python.
# Written by Lars Buitinck. This code is in the public domain.
#
# The main program runs the clustering algorithm on a bunch of text documents
# specified as command-line arguments. These documents are first converted to
# sparse vectors, represented as lists of (index, value) pairs.
from collections import defaultdict
@thorikawa
thorikawa / detect_multiscale.cpp
Created January 15, 2013 09:36
Simple example for CascadeClassifier.detectMultiScale
View detect_multiscale.cpp
#include <opencv2/opencv.hpp>
#include <vector>
using namespace cv;
using namespace std;
int main () {
Mat img = imread("lena.jpg");
CascadeClassifier cascade;
if (cascade.load("haarcascade_frontalface_alt.xml")) {
@amueller
amueller / gist:4299381
Created December 15, 2012 21:26
Plotting PCAs of pairs of MNIST digit classes
View gist:4299381
import numpy as np
import matplotlib.pyplot as plt
from itertools import product
from sklearn.decomposition import RandomizedPCA
from sklearn.datasets import fetch_mldata
from sklearn.utils import shuffle
mnist = fetch_mldata("MNIST original")
X_train, y_train = mnist.data[:60000] / 255., mnist.target[:60000]