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Ezequiel Erbaro alejandrodumas

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  • Buenos Aires, Argentina
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@karpathy
karpathy / min-char-rnn.py
Last active May 19, 2024 16:44
Minimal character-level language model with a Vanilla Recurrent Neural Network, in Python/numpy
"""
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)
@andreyvit
andreyvit / tmux.md
Created June 13, 2012 03:41
tmux cheatsheet

tmux cheat sheet

(C-x means ctrl+x, M-x means alt+x)

Prefix key

The default prefix is C-b. If you (or your muscle memory) prefer C-a, you need to add this to ~/.tmux.conf:

remap prefix to Control + a

@karpathy
karpathy / pg-pong.py
Created May 30, 2016 22:50
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
@desandro
desandro / require-js-discussion.md
Created January 31, 2013 20:26
Can you help me understand the benefit of require.js?

I'm having trouble understanding the benefit of require.js. Can you help me out? I imagine other developers have a similar interest.

From Require.js - Why AMD:

The AMD format comes from wanting a module format that was better than today's "write a bunch of script tags with implicit dependencies that you have to manually order"

I don't quite understand why this methodology is so bad. The difficult part is that you have to manually order dependencies. But the benefit is that you don't have an additional layer of abstraction.

@turnersr
turnersr / tda.md
Created January 28, 2014 14:19
Resources for Topological Data Analysis
@chetan
chetan / yardoc_cheatsheet.md
Last active May 10, 2024 02:53
YARD cheatsheet
@subfuzion
subfuzion / redis-autostart-osx.md
Last active April 26, 2024 21:40
redis auto start OS X

Install with Homebrew

brew install redis

Set up launchctl to auto start redis

$ ln -sfv /usr/local/opt/redis/*.plist ~/Library/LaunchAgents

/usr/local/opt/redis/ is a symlink to /usr/local/Cellar/redis/x.y.z (e.g., 2.8.7)

@tinabeans
tinabeans / template.html
Last active February 13, 2024 09:18
A super-barebones single-column responsive email template, assuming a max-width of 540px. Read about it on the Fog Creek blog.
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html>
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>Single-Column Responsive Email Template</title>
<style>
@media only screen and (min-device-width: 541px) {
.content {
@ndarville
ndarville / business-models.md
Last active January 13, 2024 17:27
Business models based on the compiled list at http://news.ycombinator.com/item?id=4924647. I find the link very hard to browse, so I made a simple version in Markdown instead.

Business Models

Advertising

Models Examples
Display ads Yahoo!
Search ads Google
@baraldilorenzo
baraldilorenzo / readme.md
Last active November 21, 2023 22:41
VGG-16 pre-trained model for Keras

##VGG16 model for Keras

This is the Keras model of the 16-layer network used by the VGG team in the ILSVRC-2014 competition.

It has been obtained by directly converting the Caffe model provived by the authors.

Details about the network architecture can be found in the following arXiv paper:

Very Deep Convolutional Networks for Large-Scale Image Recognition

K. Simonyan, A. Zisserman