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@mxcl
mxcl / uninstall_homebrew.sh
Created August 26, 2011 11:25
Uninstall Homebrew
#!/bin/sh
# Just copy and paste the lines below (all at once, it won't work line by line!)
# MAKE SURE YOU ARE HAPPY WITH WHAT IT DOES FIRST! THERE IS NO WARRANTY!
function abort {
echo "$1"
exit 1
}
set -e

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

@FiloSottile
FiloSottile / 32.asm
Last active May 16, 2024 19:56
NASM Hello World for x86 and x86_64 Intel Mac OS X (get yourself an updated nasm with brew)
; /usr/local/bin/nasm -f macho 32.asm && ld -macosx_version_min 10.7.0 -o 32 32.o && ./32
global start
section .text
start:
push dword msg.len
push dword msg
push dword 1
mov eax, 4
@JadenGeller
JadenGeller / Matrix Examples.swift
Last active August 10, 2023 10:03
Matrices in Swift
// Numerical matrix examples
let x: Matrix = [[10, 9, 8], [3, 2, 1]]
let y: Matrix = [[1, 2, 3], [4, 5, 6]]
let z: Matrix = [[1, 2], [3, 4], [5, 6]]
x + y // [[11, 11, 11], [7, 7, 7]]
x * y // [[10, 18, 24], [12, 10, 6]]
2 * x // [[20, 18, 16], [6, 4, 2]]
y ** z // [[22, 28], [49, 64]]
@karpathy
karpathy / gist:587454dc0146a6ae21fc
Last active May 16, 2024 19:55
An efficient, batched LSTM.
"""
This is a batched LSTM forward and backward pass
"""
import numpy as np
import code
class LSTM:
@staticmethod
def init(input_size, hidden_size, fancy_forget_bias_init = 3):
@mailletf
mailletf / gist:3484932dd29d62b36092
Created April 18, 2015 16:55
Display a mel-scaled power spectrogram using librosa
# Mostly taken from: http://nbviewer.ipython.org/github/bmcfee/librosa/blob/master/examples/LibROSA%20demo.ipynb
import librosa
import matplotlib.pyplot as plt
# Load sound file
y, sr = librosa.load("filename.mp3")
# Let's make and display a mel-scaled power (energy-squared) spectrogram
S = librosa.feature.melspectrogram(y, sr=sr, n_mels=128)
@karpathy
karpathy / min-char-rnn.py
Last active May 30, 2024 23:33
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)
@yusugomori
yusugomori / Dropout.py
Last active March 13, 2023 05:46
Dropout Neural Networks (with ReLU)
# -*- coding: utf-8 -*-
import sys
import numpy
numpy.seterr(all='ignore')
'''
@jiaaro
jiaaro / _INSTRUCTIONS.md
Last active January 22, 2024 17:47
Using Swift libraries in Python

Using Swift libraries in Python

So... this is obviously totally, 100%, like for. real. not. supported. by. Apple. …yet?

But still... I thought it was pretty badass. And, seeing how there's already a Swift buildpack for Heroku you could move some slow code into Swift can call it as a library function. But, you know, not in production or anything. That would be silly, right?

Now, having said that, the actual Python/Swift interop may have bugs. I'll leave that as an exercise to the reader.

How to get Python code calling Swift functions:

@yrevar
yrevar / imagenet1000_clsidx_to_labels.txt
Last active May 10, 2024 05:27
text: imagenet 1000 class idx to human readable labels (Fox, E., & Guestrin, C. (n.d.). Coursera Machine Learning Specialization.)
{0: 'tench, Tinca tinca',
1: 'goldfish, Carassius auratus',
2: 'great white shark, white shark, man-eater, man-eating shark, Carcharodon carcharias',
3: 'tiger shark, Galeocerdo cuvieri',
4: 'hammerhead, hammerhead shark',
5: 'electric ray, crampfish, numbfish, torpedo',
6: 'stingray',
7: 'cock',
8: 'hen',
9: 'ostrich, Struthio camelus',