hereismari

hereismari

hereismari

import torch
import pandas as pd
import numpy as np
import syft as sy
import copy
hook = sy.TorchHook(torch)
from torch import nn
import torch.nn.functional as F
from torch import optim

hereismari

function Square(props) {
  return (
    <button className="square" onClick={props.onClick} style={ props.highlight ? { background: 'green' } : { background: 'white' } }>
      {props.value}
    </button>
  );
}


class Board extends React.Component {

hereismari

# -*- coding: utf-8 -*-
"""nlp_estimators.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1oXjNYSJ3VsRvAsXN4ClmtsVEgPW_CX_c

Classifying text with TensorFlow Estimators
===

hereismari

hereismari

Deploying Flask on Heroku

Here ~/ means the repository main folder.

1. Define ~/requirements.txt with all your Python Dependencies. For instance:

flask
numpy
pandas

hereismari

% funcao auxiliar que corta uma palavra adequadamente para flexiona-la
reduzir(VERBO, VERBO_REDUZIDO, N) :-
	% tamanho do verbo eh TAM_VERBO
	string_length(VERBO, TAM_VERBO), 
	% devemos retirar as ultimas N letras do verbo  
	FIM_VERBO is TAM_VERBO-N,
	% o resultado eh guardado em VERBO_REDUZIDO
	sub_atom(VERBO, 0, FIM_VERBO, _, VERBO_REDUZIDO).

% EU

hereismari

Setting up a MSI laptop with GPU (gtx1060)

Installing Ubuntu 18.04, CUDA, CDNN, Pytorch and TensorFlow

Installing Ubuntu 18.04

Get Image

https://tutorials.ubuntu.com/tutorial/tutorial-create-a-usb-stick-on-ubuntu#0

Install (solving issues)

hereismari

import json
from urllib2 import Request, urlopen

html = Request('http://codeforces.com/api/problemset.problems')
response = urlopen(html)
x = response.read()
data = json.loads(x)  
print len(data['result']['problems'])  # dict with data from ~ 3912 problems

html = Request('http://codeforces.com/api/user.ratedList')