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Web Site Terms and Conditions of Use | |
1. Terms | |
By accessing this web site, you are agreeing to be bound by these web site Terms and Conditions of Use, all applicable laws and regulations, and agree that you are responsible for compliance with any applicable local laws. If you do not agree with any of these terms, you are prohibited from using or accessing this site. The materials contained in this web site are protected by applicable copyright and trade mark law. | |
2. Use License | |
Permission is granted to temporarily download one copy of the materials (information or software) on HorosPubers's web site for personal, non-commercial transitory viewing only. This is the grant of a license, not a transfer of title, and under this license you may not: | |
modify or copy the materials; |
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import tensorflow as tf | |
from tensorflow.examples.tutorials.mnist import input_data | |
""" | |
input>weight>hidden layer 1 (actv funct)>weight>hidden l2 (actv fucnt)>weights>output lacer | |
compare output to intended output>cost function(cross entropy) | |
optimization funvtion(omptimier)>minimize cost(AdamOptimizer...SGD,AdaGrad) | |
feed forward + backprob = epoch |
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import nltk | |
from nltk.tokenize import word_tokenize | |
from nltk.stem import WordNetLemmatizer | |
import numpy as np | |
import pickle | |
import random | |
from collections import Counter | |
lemmatizer = WordNetLemmatizer() | |
hm_lines = 1000000 |
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% This is LLNCS.DEM the demonstration file of | |
% the LaTeX macro package from Springer-Verlag | |
% for Lecture Notes in Computer Science, | |
% version 2.4 for LaTeX2e as of 16. April 2010 | |
% | |
\documentclass{llncs} | |
% | |
\usepackage{makeidx} % allows for indexgeneration | |
\usepackage{llncsdoc} | |
\usepackage{remreset} |
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From now on well pay 5% of the contract size to the guys getting the job(negotiating posting our articels ensuring payment etc.). | |
3% will go to the squad leader and 2% to the squad assitants(such that we have at least 2 responsible actors in each squad). | |
10% will go to our SM fonds which consist of multiple things such as insurance(for not payed jobs) and lotteries for the members to motivate individuals etc. | |
A squad consist of a geographically close and lingustically united group of at least 5 members. The global mixed squad is just a place to gahter newcomers. | |
I will add all of you to the newspaper [Swiss Mercenaries] such that we can post articels under one brand. Please translate the articel | |
https://gist.github.com/SandroLuck/f372fdca3d0abe64244d2ce8bcfadb5e into your respective language and consider posting it roughlty every ~24h. | |
fell free to add/change aspects of it which might be good for the respective language/culture . | |
Once you are hired make sure we can trust the entitiy to pay us once the |
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[center][img]http://up.picr.de/31166645so.jpg[/img][/center] | |
[size=25px][b]A brief history of the Swiss Guard[/b][/size] | |
Due to the long tradition of Swiss mercenaries I would like to present you a brief history of the Swiss Guard. This is just a small overview about the most important moments in the history of the Papal guard. | |
[b]1506 - Founding[/b] | |
For more than 500 years, the Swiss Guard has been serving the popes and guarding the Vatican. It all began in 1506, when the first Swiss arrived at the request of Pope Julius II. The choice of the Pope to recruit Swiss mercenaries did not come without reason. The Confederate soldiers were considered to be invincible because of their courage, their noble disposition and their proverbial loyalty. | |
[b]1527 - Sacco di Roma[/b] | |
On the morning of May 6, 1527, Captain-General Bourbon ordered the attack from his headquarters, the Monastery of Sant'Onofrio on the Gianicolo. At the Porta del Torrione he was mortally wounded when he started to storm the city wall. After a |
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[size=25px][b]Your Favorite RR weapon?[/b][/size] | |
[right][b]The Award Press[/b][/right] | |
[center]The Award Press is looking for what your favorite weapon is!! | |
[/center] | |
[center][b]Subscribe to the Award Press for more daily nonsense and votings![/b][/center] | |
[center][b]This articel was sponsored by: The Swiss Mercenaries http://m.rivalregions.com/#news/show/431783 | |
[/b][/center] | |
- | |
[vote]Your favorite Weapon[/vote] |
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[size=50px][b]US-study says countryball is underrated![/b][/size] | |
[right][size=25px][b]The Award Press[/b][/size][/right] | |
[img]https://i.redd.it/imb7e908glpz.png[/img] | |
[img]https://i.imgur.com/ZaC728x.png[/img] | |
[img]https://i.imgur.com/XLAW4Ys.png[/img] | |
[img]https://i.redd.it/4khw2hyzcfey.png[/img] | |
[center][rr][size=35px][url=http://rivalregions.com/#newspaper/show/129561]SUBSCRIBE[/url] FOR MORE![/size][/rr] [/center] | |
[center][size=30px][b]This articel was sponsored by (click images):[/b][/size][/center] |
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http://rivalregions.com/#slide/join/121468/c0fdb730865c5362a7f402d1faa477f1 |
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import torch.nn.functional as F | |
from pytorch_lightning import seed_everything, LightningModule, Trainer | |
from pytorch_lightning.callbacks import EarlyStopping | |
from torch import nn, optim, rand, sum as tsum, reshape, save | |
from torch.utils.data import DataLoader, Dataset | |
SAMPLE_DIM = 21000 | |
class CustomDataset(Dataset): | |
def __init__(self, samples=42): |
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