PurpleVibe32

Install VMWare Workstation PRO 17 (Read it right. PRO!)
Also, these keys might also work with VMWare Fusion 13 PRO. Just tested it.

Sub to me on youtube pls - PurpleVibe32
if you want more keys - call my bot on telegram. @purector_bot (THE BOT WONT REPLY ANYMORE) - Or: https://cdn.discordapp.com/attachments/1040615179894935645/1074016373228978277/keys.zip - the password in the zip is 102me.
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This gist can get off at any time.
PLEASE, DONT COPY THIS. IF YOU FORK IT, DONT EDIT IT.
*If you have a problem comment and people will try to help you!
*No virus

mohapatras

import numpy as np
from sklearn.metrics import roc_curve

def sensivity_specifity_cutoff(y_true, y_score):
    '''Find data-driven cut-off for classification
    
    Cut-off is determied using Youden's index defined as sensitivity + specificity - 1.
    
    Parameters
    ----------

mcvarer

#!/bin/bash
## This gist contains instructions about cuda v11.2 and cudnn 8.1 installation in Ubuntu 18.04 for PyTorch

#############################################################################################
##### forked by : https://gist.github.com/Mahedi-61/2a2f1579d4271717d421065168ce6a73 ########
#############################################################################################


### steps ####
# verify the system has a cuda-capable gpu

kmhofmann

Installing the NVIDIA driver, CUDA and cuDNN on Linux (Ubuntu 20.04)

This is a companion piece to my instructions on building TensorFlow from source. In particular, the aim is to install the following pieces of software

• NVIDIA graphics card driver (v450.57)
• CUDA (v11.0.2)
• cuDNN (v8.0.2.39)

on an Ubuntu Linux system, in particular Ubuntu 20.04.

moodoki

import os, argparse

import tensorflow as tf
from tensorflow.python.framework import graph_util

dir = os.path.dirname(os.path.realpath(__file__))

def freeze_graph(model_folder, output_nodes='y_hat', 
                 output_filename='frozen-graph.pb', 
                 rename_outputs=None):

sunsided

import argparse
import os
import sys
from typing import Iterable
import tensorflow as tf


parser = argparse.ArgumentParser()
parser.add_argument('file', type=str, help='The file name of the frozen graph.')
args = parser.parse_args()

joepie91

Don't use VPN services.

No, seriously, don't. You're probably reading this because you've asked what VPN service to use, and this is the answer.

Note: The content in this post does not apply to using VPN for their intended purpose; that is, as a virtual private (internal) network. It only applies to using it as a glorified proxy, which is what every third-party "VPN provider" does.

• A Russian translation of this article can be found here, contributed by Timur Demin.
• A Turkish translation can be found here, contributed by agyild.
• There's also this article about VPN services, which is honestly better written (and has more cat pictures!) than my article.

erogol

FROM: http://benanne.github.io/2015/03/17/plankton.html

Meta-Tricks:
	- Use %10 for validation with STRATIFIED SAMPLING (my mistake)
	- Cyclic Pooling 
	- Leaky ReLU = max(x, a*x) learned a
		- reduces overfitting with a ~= 1/3
	- Orthogonal initialization http://arxiv.org/pdf/1312.6120v3.pdf
	- Use larger weight decay for larger models since otherwise some layers might diverge

zacstewart

import os
import numpy
from pandas import DataFrame
from sklearn.feature_extraction.text import CountVectorizer
from sklearn.naive_bayes import MultinomialNB
from sklearn.pipeline import Pipeline
from sklearn.cross_validation import KFold
from sklearn.metrics import confusion_matrix, f1_score

NEWLINE = '\n'