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zyxue / SRNN-vs-LSTM
Created Apr 17, 2018
Train a single-neuron RNN to compare performance of vanilla RNN and LSTM on information latching
import matplotlib.pyplot as plt
import numpy as np
from keras.models import Model
from keras.layers import Input, LSTM, Dense, SimpleRNN
N = 10000
num_repeats = 30
num_epochs = 5
# sequence length options
View spark-custom-aggregator
import scala.collection.mutable.Map
import org.apache.spark.sql.expressions.Aggregator
import org.apache.spark.sql.Encoder
import org.apache.spark.sql.Encoders
import spark.implicits._
import org.apache.spark.sql.types._
zyxue / grid-cv
Last active Sep 27, 2017
demonstration of sklearn GridSearchCV spawning multiple threads on linux
View grid-cv
# related SF question:
import numpy as np
from sklearn.linear_model import LogisticRegression
from sklearn.model_selection import StratifiedKFold
from sklearn.model_selection import GridSearchCV
Cs = 10 ** np.arange(-2, 2, 0.1)
zyxue /
Last active Dec 4, 2018
python EDA imports
import os
import io
import gzip
import time
import sys
import glob
import json
import re
import csv
import datetime
def execute(cmd, flag_file=None, msg_id='', debug=False):
:param cmd: should never inlcude pipe or redirection, which would requires
a new shell process
This execute logs all stdout and stderr, which could look funny, especially
when it comes to tools like aspc and wget
"""'executing: {0}'.format(cmd))
# todo: should check whether cmdsp includes pipe or redirection here