FavioVazquez

FavioVazquez

FavioVazquez

install.packages("remotes")
remotes::install_github("JohnCoene/g2r")

# So normally this is what you do for getting a plot with ggplot2

library(ggplot2)

ggplot(iris, aes(Petal.Length, Petal.Width, color = Species)) +
  geom_point() +
  facet_wrap(.~Species)

FavioVazquez

id,conversation_id,created_at,date,time,timezone,user_id,username,name,place,tweet,mentions,urls,photos,replies_count,retweets_count,likes_count,location,hashtags,link,retweet,quote_url,video
1124775205698719744,1124775205698719744,1557002281000,2019-05-04,15:38:01,CDT,788898706586275840,tdatascience,Towards Data Science,,Optimal Control: LQR by @vlastelicap https://buff.ly/2ZT45ud ,['vlastelicap'],['https://buff.ly/2ZT45ud'],[],0,0,1,,[],https://twitter.com/TDataScience/status/1124775205698719744,,,0
1124733938625384448,1124733938625384448,1556992442000,2019-05-04,12:54:02,CDT,788898706586275840,tdatascience,Towards Data Science,,Who owns your health data?  https://buff.ly/2Ywezz0  🖊by @jaynew_l #healthcare #BigData #TDSPick 🎲 pic.twitter.com/C2BbVyvyky,['jaynew_l'],['https://buff.ly/2Ywezz0'],['https://pbs.twimg.com/media/D5vbjoVW4AA0FzV.jpg'],0,1,0,,"['#healthcare', '#bigdata', '#tdspick']",https://twitter.com/TDataScience/status/1124733938625384448,,,0
1124697946887532544,1124697946887532544,1556983861000

FavioVazquez

FavioVazquez

FavioVazquez

import tensorflow as tf

__weights_dict = dict()

is_train = False

def load_weights(weight_file):
    import numpy as np

    if weight_file == None:

FavioVazquez

import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F

__weights_dict = dict()

def load_weights(weight_file):
    if weight_file == None:
        return

FavioVazquez

'''Train a simple deep CNN on the CIFAR10 small images dataset.

GPU run command:
    THEANO_FLAGS=mode=FAST_RUN,device=gpu,floatX=float32 python cifar10_cnn.py

It gets down to 0.65 test logloss in 25 epochs, and down to 0.55 after 50 epochs.
(it's still underfitting at that point, though).

Note: the data was pickled with Python 2, and some encoding issues might prevent you
from loading it in Python 3. You might have to load it in Python 2,

FavioVazquez