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initbrain /
Last active Jan 8, 2017
Python Wi-Fi Positioning System, use Google Maps Geolocation API, tested on GNU/Linux (require iw) and Mac OS X (require airport), special thanks go to contributors!
nicolov / .gitignore
Last active Jul 2, 2020
Car speed estimation from a windshield camera
View .gitignore
karpathy /
Created May 30, 2016
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym
# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward
ewnd9 /
Last active Jun 28, 2020
google's deepdream ubuntu installation
# sources
# ~2gb dependencies
mkdir deep-dream && cd deep-dream
sudo apt-get install subversion cmake
johnynek / AliceInAggregatorLand.scala
Last active Jun 5, 2020
A REPL Example of using Aggregators in scala
View AliceInAggregatorLand.scala
* To get started:
* git clone
* cd algebird
* ./sbt algebird-core/console
* Let's get some data. Here is Alice in Wonderland, line by line
syhw /
Last active Apr 29, 2020
A simple deep neural network with or w/o dropout in one file.
A deep neural network with or w/o dropout in one file.
License: Do What The Fuck You Want to Public License
import numpy, theano, sys, math
from theano import tensor as T
from theano import shared
from theano.tensor.shared_randomstreams import RandomStreams
johnynek / scalding_alice.scala
Created Jul 18, 2014
Learn Scalding with Alice
View scalding_alice.scala
git clone
cd scalding
./sbt scalding-repl/console
val alice = Source.fromURL("").getLines
// Add the line numbers, which we might want later
val aliceLineNum = alice.zipWithIndex.toList
debasishg / gist:8172796
Last active Jun 24, 2020
A collection of links for streaming algorithms and data structures
View gist:8172796
  1. General Background and Overview
azymnis / ItemSimilarity.scala
Created Dec 13, 2013
Approximate item similarity using LSH in Scalding.
View ItemSimilarity.scala
import com.twitter.scalding._
import com.twitter.algebird.{ MinHasher, MinHasher32, MinHashSignature }
* Computes similar items (with a string itemId), based on approximate
* Jaccard similarity, using LSH.
* Assumes an input data TSV file of the following format:
* itemId userId
View Makefile
obj-m += rootkit.o
make -C /lib/modules/$(shell uname -r)/build M=$(PWD) modules
make -C /lib/modules/$(shell uname -r)/build M=$(PWD) clean
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