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It is by will alone I set my mind in motion.

Alexander Veysov snakers4

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It is by will alone I set my mind in motion.
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@snakers4
snakers4 / PyTorchMlP.py
Created May 28, 2018 07:48
Playing with MLP + embeddings in PyTorch
import torch
import torch.nn as nn
from torch.autograd import Variable
class NaiveClassifier(nn.Module):
def __init__(self,
cat_sizes=None,
numerical_features=117,
mlp_sizes=[1024,2048,1024,512,256,128,2],
embedding_factor=3,
@snakers4
snakers4 / multiprocessing_tqdm.py
Last active May 25, 2018 10:13
Using tqdm with multiprocessing
import tqdm
import pandas as pd
import numpy as np
from multiprocessing import Pool
import os
# drop all the unknown points and all closed points
# for each SK_ID_CURR calculate the counts of time in each status
# normalize by the max len (we know of) in any of the meaningful statuses
@snakers4
snakers4 / abstractions.py
Last active May 27, 2022 07:12
My XGB boilerplate
# https://www.analyticsvidhya.com/blog/2016/03/complete-guide-parameter-tuning-xgboost-with-codes-python/
#Import libraries:
import pandas as pd
import numpy as np
import xgboost as xgb
from xgboost.sklearn import XGBClassifier
from sklearn import cross_validation, metrics #Additional scklearn functions
from sklearn.grid_search import GridSearchCV #Perforing grid search
import matplotlib.pylab as plt
@snakers4
snakers4 / Dockerfile
Last active February 22, 2018 09:30
Dockerfile update
# add 7z tar and zip archivers
FROM nvidia/cuda:9.0-cudnn7-devel
RUN apt-get update && apt-get install -y openssh-server
RUN mkdir /var/run/sshd
RUN echo 'root:Ubuntu@41' | chpasswd
RUN sed -i 's/PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
# SSH login fix. Otherwise user is kicked off after login
RUN sed 's@session\s*required\s*pam_loginuid.so@session optional pam_loginuid.so@g' -i /etc/pam.d/sshd
import torchvision.models as models
import torch
import torch.nn as nn
class FineTuneModel(nn.Module):
def __init__(self,
original_model,
arch,
num_classes,
freeze
@snakers4
snakers4 / DS NN guidelines
Created October 19, 2017 07:39
Complete system installation for Data Science / Neural Networks from scratch / bare metal (assuming you have assembled the PC)
# BASIC SYSTEM SETUP
# First donwload Ubuntu iso file from https://www.ubuntu.com/download/desktop
# Use 16.04 LTS (17 is also ok, but it's better to use LTS versions, also 18 will be very mature in terms of systemd)
# Dowload Linux live USB creator and install the iso to your USB stick https://www.linuxliveusb.com
# Boot your system, go to BIOS on boot (usually Del) or boot menu (usually F12) and choose your USB stick as boot medium
# Install Linux (these steps can be omitted if clean Ubuntu installation is provided as service by admins / cloud provider / etc)
# Minor trick unplug ALL of your hard disks (unless you are an avanced user) except for the disk for your system
FROM nvidia/cuda:8.0-cudnn6-devel
RUN apt-get update && apt-get install -y openssh-server
RUN mkdir /var/run/sshd
RUN echo 'root:YOUR_PASSWORD' | chpasswd
RUN sed -i 's/PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config
# SSH login fix. Otherwise user is kicked off after login
RUN sed 's@session\s*required\s*pam_loginuid.so@session optional pam_loginuid.so@g' -i /etc/pam.d/sshd
from keras.models import Model
from keras.layers import Input, concatenate, Conv2D, MaxPooling2D, Activation, UpSampling2D, BatchNormalization,multiply
from keras.optimizers import RMSprop
from model.losses import bce_dice_loss, dice_loss, weighted_bce_dice_loss, weighted_dice_loss, dice_coeff
import params
orig_width = 1918
orig_height = 1280
<p></p><p><img src="https://pics.spark-in.me/upload/7b09411ab7b91bc8da7e79c763311795.jpg" style="width: 700px;"></p><p><span style="font-style: italic;">Как всегда надо начать с заманчивой картинки, но не пояснять ее смысл!</span></p><hr><p></p><p style="text-align: justify; ">Пару дней назад ко мне обратился далекий знакомый, мол у нас политесы в компании и мы не можем никак выбрать направление развития. Ситуация типичная - <span style="font-weight: bold;">лебедь, рак и щука</span> и надо бы очень быстро <span style="font-weight: bold;">проанализировать сайты его конкурентов</span>, вот держи картинку со списком самых крупных компаний в этой сфере. Оказалось, что конкуренты из сферы форекса. Это меня смутило, но не остановило. Я посмотрел на их сайты (а, забегая вперед, некоторые из них просто огромны - миллионы страниц) и тут у меня родилась гениальная идея.</p><p style="text-align: justify; ">Я занимался ей пару суток почти без остановки и накопал относительно интересные результаты, которыми и хочу поделит
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