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Hello Underworld. Hello 人工稚能.

Lei Mao leimao

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Hello Underworld. Hello 人工稚能.
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@mieitza
mieitza / mongo_to_csv.py
Created Jan 3, 2018 — forked from wixb50/mongo_to_csv.py
python mongo to csv use pandas.
View mongo_to_csv.py
# @Author: xiewenqian <int>
# @Date: 2016-11-28T20:35:09+08:00
# @Email: wixb50@gmail.com
# @Last modified by: int
# @Last modified time: 2016-12-01T19:32:48+08:00
import pandas as pd
from pymongo import MongoClient
@ledmaster
ledmaster / MultipleTimeSeriesForecasting.ipynb
Last active Apr 23, 2022
How To Predict Multiple Time Series With Scikit-Learn (With a Sales Forecasting Example)
View MultipleTimeSeriesForecasting.ipynb
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View spectral_param.ipynb
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@omimo
omimo / create_hellotensor.py
Last active Feb 5, 2021
A simple example for saving a tensorflow model and preparing it for using on Android
View create_hellotensor.py
# Create a simple TF Graph
# By Omid Alemi - Jan 2017
# Works with TF <r1.0
import tensorflow as tf
I = tf.placeholder(tf.float32, shape=[None,3], name='I') # input
W = tf.Variable(tf.zeros_initializer(shape=[3,2]), dtype=tf.float32, name='W') # weights
b = tf.Variable(tf.zeros_initializer(shape=[2]), dtype=tf.float32, name='b') # biases
O = tf.nn.relu(tf.matmul(I, W) + b, name='O') # activation / output
@wangruohui
wangruohui / Install NVIDIA Driver and CUDA.md
Last active May 11, 2022
Install NVIDIA Driver and CUDA on Ubuntu / CentOS / Fedora Linux OS
View Install NVIDIA Driver and CUDA.md
@protrolium
protrolium / terminal-gif.md
Last active Apr 29, 2022
convert images to GIF in Terminal
View terminal-gif.md

Install ImageMagick

brew install ImageMagick

Pull specific region of frames from video file w/ ffmpeg

ffmpeg -ss 14:55 -i video.mkv -t 5 -s 480x270 -f image2 %04d.png

  • -ss 14:55 gives the timestamp where I want FFmpeg to start, as a duration string.
  • -t 5 says how much I want FFmpeg to decode, using the same duration syntax as for -ss.
  • -s 480x270 tells FFmpeg to resize the video output to 480 by 270 pixels.
  • -f image2 selects the output format, a series of still images — make sure there are leading zeros in filename.
@karpathy
karpathy / pg-pong.py
Created May 30, 2016
Training a Neural Network ATARI Pong agent with Policy Gradients from raw pixels
View pg-pong.py
""" Trains an agent with (stochastic) Policy Gradients on Pong. Uses OpenAI Gym. """
import numpy as np
import cPickle as pickle
import gym
# hyperparameters
H = 200 # number of hidden layer neurons
batch_size = 10 # every how many episodes to do a param update?
learning_rate = 1e-4
gamma = 0.99 # discount factor for reward
@zoltanctoth
zoltanctoth / pyspark-udf.py
Last active Apr 29, 2022
Writing an UDF for withColumn in PySpark
View pyspark-udf.py
from pyspark.sql.types import StringType
from pyspark.sql.functions import udf
maturity_udf = udf(lambda age: "adult" if age >=18 else "child", StringType())
df = spark.createDataFrame([{'name': 'Alice', 'age': 1}])
df.withColumn("maturity", maturity_udf(df.age))
df.show()
@ChunMinChang
ChunMinChang / remove_c_style_comments.py
Last active Apr 11, 2022
Python: Remove C/C++ style comments #parser
View remove_c_style_comments.py
#!/usr/bin/python
import re
import sys
def removeComments(text):
""" remove c-style comments.
text: blob of text with comments (can include newlines)
returns: text with comments removed
"""
pattern = r"""
@baraldilorenzo
baraldilorenzo / readme.md
Last active May 17, 2022
VGG-16 pre-trained model for Keras
View readme.md

##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