Skip to content

Instantly share code, notes, and snippets.

View urinieto's full-sized avatar

Oriol Nieto urinieto

View GitHub Profile
Loading
Sorry, something went wrong. Reload?
Sorry, we cannot display this file.
Sorry, this file is invalid so it cannot be displayed.
@gabrieleangeletti
gabrieleangeletti / rbm_after_refactor.py
Last active July 27, 2021 14:32
Restricted Boltzmann Machine implementation in TensorFlow, before and after code refactoring. Blog post: http://blackecho.github.io/blog/programming/2016/02/21/refactoring-rbm-tensor-flow-implementation.html
import tensorflow as tf
import numpy as np
import os
import zconfig
import utils
class RBM(object):
@baraldilorenzo
baraldilorenzo / readme.md
Last active September 19, 2024 23:23
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

@karpathy
karpathy / min-char-rnn.py
Last active September 18, 2024 06:45
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)