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

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

import tensorflow as tf

__weights_dict = dict()

is_train = False

def load_weights(weight_file):
    import numpy as np

    if weight_file == None:

FavioVazquez

FavioVazquez

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

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

FavioVazquez

FavioVazquez