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@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

# coding: utf-8
# Imports
import os
import cPickle
import numpy as np
import theano
import theano.tensor as T
@cbaziotis
cbaziotis / Attention.py
Last active March 28, 2023 11:50
Keras Layer that implements an Attention mechanism for temporal data. Supports Masking. Follows the work of Raffel et al. [https://arxiv.org/abs/1512.08756]
from keras import backend as K, initializers, regularizers, constraints
from keras.engine.topology import Layer
def dot_product(x, kernel):
"""
Wrapper for dot product operation, in order to be compatible with both
Theano and Tensorflow
Args:
@kachayev
kachayev / topological.py
Last active December 30, 2022 10:21
Topological sort with Python (using DFS and gray/black colors)
# Simple:
# a --> b
# --> c --> d
# --> d
graph1 = {
"a": ["b", "c", "d"],
"b": [],
"c": ["d"],
"d": []
}
.
├── actions
├── stores
├── views
│   ├── Anonymous
│   │   ├── __tests__
│   │   ├── views
│   │   │   ├── Home
│   │   │   │   ├── __tests__
│   │   │   │   └── Handler.js
@chris-chris
chris-chris / simple_gradient_descent.py
Last active November 14, 2021 04:25
simple 1-step gradient descent
# From udacity Machine Learning Nanodegree course
import numpy as np
# Define sigmoid function
def sigmoid(x):
return 1/(1+np.exp(-x))
# Derivative of the sigmoid function
def sigmoid_derivative(x):
@rrag
rrag / .block
Last active August 19, 2019 11:06
CandleStickChart with React StockCharts
license: MIT
height: 420
@j-min
j-min / RNN_hunkim's_tutorial_BasicRNNCell.ipynb
Last active December 11, 2018 02:06
TensorFlow 0.9 implementation of BasicRNNCell based on hunkim's tutorial
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Used dueling network architecture with Q-learning, as outlined in this paper:

Dueling Network Architectures for Deep Reinforcement Learning
Ziyu Wang, Tom Schaul, Matteo Hessel, Hado van Hasselt, Marc Lanctot, Nando de Freitas
http://arxiv.org/abs/1511.06581

Command line:

python duel.py CartPole-v0 --gamma 0.995