felipessalvatore

import numpy as np
import tensorflow as tf

NUM_THREADS = 4

data = np.array([[0.2, 0.3], [0.4, 0.9], [0.8, -1.2], [-1.3, -0.2]])
target = np.array([1, 0, 1, 0])

queue = tf.FIFOQueue(capacity=3,
                     dtypes=[tf.float32, tf.int32],

felipessalvatore

# range_input_producer(
#                      limit,
#                      num_epochs=None,
#                      shuffle=True,
#                      seed=None,
#                      capacity=32,
#                      shared_name=None,
#                      name=None)

# Produces the integers from 0 to limit-1 in a queue.

felipessalvatore

# strided_slice(
#     input_,
#     begin,
#     end,
#     strides=None,
#     begin_mask=0,
#     end_mask=0,
#     ellipsis_mask=0,
#     new_axis_mask=0,
#     shrink_axis_mask=0,

felipessalvatore

import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
from matplotlib import rc

sns.set_style("darkgrid")

# for using latex in plt it requires one installation:
# $ sudo apt install dvipng
rc('font', **{'family': 'sans-serif', 'sans-serif': ['Helvetica']})

felipessalvatore

Setting Jupyter in a remote computer

In REMOTE

i) create config file

$ jupyter notebook --generate-config

ii) create password

felipessalvatore

from sklearn import linear_model
import numpy as np
import matplotlib.pyplot as plt

# generating fake linear data. 
# Where x = square meter, y = house price

cond = False

while not cond:

felipessalvatore

import matplotlib.pyplot as plt
from datetime import date

#data


logic_tuple =  [(1936, 3), (1937, 6), (1938, 3), (1939, 5),
  (1940, 2), (1941, 2), (1942, 7), (1943, 1),
  (1944, 2), (1945, 2), (1947, 2), (1948, 4),
  (1949, 7), (1950, 3), (1951, 2), (1952, 5),

felipessalvatore

from nltk.translate.bleu_score import modified_precision

pt = "em plano aberto, a cidade parece linda"

ref = "in a wide shot, the city looks beautiful"

c1 = "in the open, the city looks beautiful"

c2 = "in open plan, the city looks gorgeous"

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import cv2
img = cv2.imread("0.png")

font                   = cv2.FONT_HERSHEY_PLAIN
bottomLeftCornerOfText = (15,25)
fontScale              = 1
fontColor              = (255,25,55)
lineType               = 2

cv2.putText(img,"""up: 0.02""", 

felipessalvatore

Directional Derivative
http://tutorial.math.lamar.edu/Classes/CalcIII/DirectionalDeriv.aspx
https://www.ime.unicamp.br/~valle/Teaching/MA211/Aula6.pdf