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Johannes Filter jfilter

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@yang-zhang
yang-zhang / multi-face.ipynb
Last active December 27, 2023 05:28
Multi-task Deep Learning Experiment using fastai Pytorch
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@bittlingmayer
bittlingmayer / ft_wiki_preproc.py
Last active March 4, 2019 22:56
fastText pre-trained vectors preprocessing [moved to ftio.wiki.preproc - pip install ftio / https://github.com/SignalN/ftio]
# See https://github.com/facebookresearch/fastText/blob/master/get-wikimedia.sh
#
# From https://github.com/facebookresearch/fastText/issues/161:
#
# We now have a script called 'get-wikimedia.sh', that you can use to download and
# process a recent wikipedia dump of any language. This script applies the preprocessing
# we used to create the published word vectors.
#
# The parameters we used to build the word vectors are the default skip-gram settings,
# except with a dimensionality of 300 as indicated on the top of the list of word
@omoindrot
omoindrot / tensorflow_finetune.py
Last active February 25, 2024 15:00
Example TensorFlow script for fine-tuning a VGG model (uses tf.contrib.data)
"""
Example TensorFlow script for finetuning a VGG model on your own data.
Uses tf.contrib.data module which is in release v1.2
Based on PyTorch example from Justin Johnson
(https://gist.github.com/jcjohnson/6e41e8512c17eae5da50aebef3378a4c)
Required packages: tensorflow (v1.2)
Download the weights trained on ImageNet for VGG:
```
wget http://download.tensorflow.org/models/vgg_16_2016_08_28.tar.gz
@panovr
panovr / finetune.py
Created March 2, 2017 23:04
Fine-tuning pre-trained models with PyTorch
import argparse
import os
import shutil
import time
import torch
import torch.nn as nn
import torch.nn.parallel
import torch.backends.cudnn as cudnn
import torch.optim
@aryeharmon
aryeharmon / ubuntu16.04-command-line-install-android-sdk
Created December 20, 2016 14:27
sudo add-apt-repository ppa:openjdk-r/ppa
sudo apt-get update
sudo apt-get install openjdk-7-jre
# install openjdk
sudo apt-get install openjdk-7-jdk
# download android sdk
wget http://dl.google.com/android/android-sdk_r24.2-linux.tgz
@jqn
jqn / react-native csrf token
Created October 21, 2016 14:21
Retrieving csrf token from a django app with react native.
componentDidMount () {
// Get cookies as a request header string
CookieManager.get("http://127.0.0.1:8000/login/", (err, res) => {
// Outputs 'user_session=abcdefg; path=/;'
fetch("http://127.0.0.1:8000/login/", {
method: "POST",
headers: {
'Accept': 'application/json',
'Content-Type': 'application/json',
@quadrismegistus
quadrismegistus / gensim_word2vec_procrustes_align.py
Last active November 16, 2023 01:57
Code for aligning two gensim word2vec models using Procrustes matrix alignment. Code ported from HistWords <https://github.com/williamleif/histwords> by William Hamilton <wleif@stanford.edu>. [NOTE: This code is DEPRECATED for latest versions of gensim. Please see instead this updated version of the code <https://gist.github.com/zhicongchen/9e23…
def smart_procrustes_align_gensim(base_embed, other_embed, words=None):
"""Procrustes align two gensim word2vec models (to allow for comparison between same word across models).
Code ported from HistWords <https://github.com/williamleif/histwords> by William Hamilton <wleif@stanford.edu>.
(With help from William. Thank you!)
First, intersect the vocabularies (see `intersection_align_gensim` documentation).
Then do the alignment on the other_embed model.
Replace the other_embed model's syn0 and syn0norm numpy matrices with the aligned version.
Return other_embed.
@internaut
internaut / pandas_crossjoin_example.py
Last active June 12, 2020 14:30
Shows how to do a cross join (i.e. cartesian product) between two pandas DataFrames using an example on calculating the distances between origin and destination cities. See https://mkonrad.net/2016/04/16/cross-join--cartesian-product-between-pandas-dataframes.html
"""
Shows how to do a cross join (i.e. cartesian product) between two pandas DataFrames using an example on
calculating the distances between origin and destination cities.
Tested with pandas 0.17.1 and 0.18 on Python 3.4 and Python 3.5
Best run this with Spyder (see https://github.com/spyder-ide/spyder)
Author: Markus Konrad <post@mkonrad.net>
April 2016
@karpathy
karpathy / min-char-rnn.py
Last active May 6, 2024 16:42
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)
@derhuerst
derhuerst / awesome-twitter-bots.md
Last active April 7, 2023 17:45
Awesome Twitter Bots