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Trying to be less wrong through the scientific method

Blake Edwards blakete

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Trying to be less wrong through the scientific method
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Set Ubuntu Nightlight Mode To Always On With Constant Temperature

  1. Set automatic schedule to false
dconf write /org/gnome/settings-daemon/plugins/color/night-light-schedule-automatic false
  1. Set start time to midnight (0.0)
@evgenyneu
evgenyneu / setup_cursor_ubuntu.md
Last active May 11, 2025 19:42
Install Cursor AI code editor on Ubuntu 24.04 LTS

Install Cursor AI editor on Ubuntu 24.04

  1. Use the Download button on www.cursor.com web site. It will download the NAME.AppImage file.

  2. Copy the .AppImage file to your Applications directory

cd ~/Downloads
mkdir -p ~/Applications
mv NAME.AppImage ~/Applications/cursor.AppImage
@luis-gonzales
luis-gonzales / mobilenetv2_layer.py
Last active December 1, 2019 05:00
Keras layer for MobileNetV2
import tensorflow as tf
from tensorflow.keras.layers import Layer, Conv2D, DepthwiseConv2D, BatchNormalization
class InvertedResidual(Layer):
def __init__(self, filters, strides, expansion_factor=6, trainable=True,
name=None, **kwargs):
super(InvertedResidual, self).__init__(trainable=trainable, name=name, **kwargs)
self.filters = filters
self.strides = strides
self.expansion_factor = expansion_factor # allowed to be decimal value
@rocking5566
rocking5566 / keras_quant.py
Last active December 8, 2020 09:40
Quantization aware training in keras
import numpy as np
import tensorflow as tf
from tensorflow.keras.datasets import mnist
from tensorflow.keras.utils import to_categorical
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense, Activation, Conv2D, Flatten
from tensorflow.keras.optimizers import RMSprop
# download the mnist to the path '~/.keras/datasets/' if it is the first time to be called
# X shape (60,000 28x28), y shape (10,000, )
@gaearon
gaearon / modern_js.md
Last active April 14, 2025 19:22
Modern JavaScript in React Documentation

If you haven’t worked with JavaScript in the last few years, these three points should give you enough knowledge to feel comfortable reading the React documentation:

  • We define variables with let and const statements. For the purposes of the React documentation, you can consider them equivalent to var.
  • We use the class keyword to define JavaScript classes. There are two things worth remembering about them. Firstly, unlike with objects, you don't need to put commas between class method definitions. Secondly, unlike many other languages with classes, in JavaScript the value of this in a method [depends on how it is called](https://developer.mozilla.org/en-US/docs/Web/Jav
import numpy as np
from keras import backend as K
from keras.models import Sequential
from keras.layers.core import Dense, Dropout, Activation, Flatten
from keras.layers.convolutional import Convolution2D, MaxPooling2D
from keras.preprocessing.image import ImageDataGenerator
from sklearn.metrics import classification_report, confusion_matrix
#Start
train_data_path = 'F://data//Train'
@joselitosn
joselitosn / pysmb.py
Created March 16, 2016 13:45
Python SMB Example
from smb.SMBConnection import SMBConnection
userID = 'user'
password = 'password'
client_machine_name = 'localpcname'
server_name = 'servername'
server_ip = '0.0.0.0'
domain_name = 'domainname'
@baraldilorenzo
baraldilorenzo / readme.md
Last active January 14, 2025 11:07
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