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View ch06_Learning_to_Classify_Text.ipynb
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View Neuropython_ex3_answer
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#연습문제 3\n",
"\n",
"###본 연습문제는 1주차 Neural Simulation 복습 및 function와 class 를 정의해보고 이를 활용해 보는 것을 목표으로 합니다.\n",
"\n",
View Build tensorflow on OSX with NVIDIA CUDA support.md

Build tensorflow on OSX with NVIDIA CUDA support (GPU acceleration)

These instructions are based on Mistobaan's gist but expanded and updated to work with the latest tensorflow OSX CUDA PR.

Requirements

OS X 10.10 (Yosemite) or newer

@bage79
bage79 / semantic_transfer_learning.py
Created Nov 14, 2017 — forked from prats226/semantic_transfer_learning.py
Sentiment classification using transfer learning
View semantic_transfer_learning.py
import collections, math, random, numpy
import tensorflow as tf
from sklearn.cross_validation import train_test_split
sentences = """hated the movie it was stupid;\ni hated it so boring;\nawesome the movie was inspiring;\nhated it what a disaster;\nwe hated the movie they were idiotic;\nhe was stupid, hated her;\nstupid movie is boring;\ninspiring ourselves, awesome;\ninspiring me, brilliant;\nwe hated it they were rubbish;\nany inspiring movie is amazing;\nit was stupid what a disaster;\nits stupid, rubbish;\nstupid, idiotic!;\nawesome great movie;\nboring, must be hated;\nhe was boring the movie was stupid;\nboring movie was a disaster;\nboth boring and rubbish;\nso boring and idiotic;\ngreat to amazing;\ndisaster, more than hated;\nbetween disaster and stupid;\ndisaster, so boring;\nawesome movie, brilliant;\ntoo awesome she was amazing;\nhe was brilliant loved it;\ndisaster, only idiotic;\nrubbish movie hated him;\nit was rubbish, why so stupid?;\nrubbish, too boring;\nrubbish, disaster!;\nrubbish, very
@bage79
bage79 / translate-srt.py
Created Apr 15, 2018 — forked from jney/translate-srt.py
translate a srt file with google translate
View translate-srt.py
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import sys,json,urllib
from pysrt import SubRipFile, SubRipItem
url_string = 'http://ajax.googleapis.com/ajax/services/language/'
def detect(text):
query = dict(v='1.0', q=text)
@bage79
bage79 / tensorflow_macos_sse41_sse42_avx_avx2_fma_cuda.md
Created Oct 10, 2017 — forked from philster/tensorflow_macos_sse41_sse42_avx_avx2_fma_cuda.md
Build TensorFlow 1.3 with SSE4.1/SSE4.2/AVX/AVX2/FMA and NVIDIA CUDA support on macOS Sierra 10.12
View tensorflow_macos_sse41_sse42_avx_avx2_fma_cuda.md

Build TensorFlow 1.3 with SSE4.1/SSE4.2/AVX/AVX2/FMA and NVIDIA CUDA support on macOS Sierra 10.12 (updated October 5, 2017)

These instructions were inspired by Mistobaan's gist, ageitgey's gist, and mattiasarro's tutorial.

Background

I always encountered the following warnings when running my scripts using the precompiled TensorFlow Python package:

W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] Th
@bage79
bage79 / string_replace_util.py
Last active Oct 16, 2019
코퍼스와 같은 말뭉치에서 정해진 단위로 문장을 나누고, 한 문장에서 특정한 패턴이 있을 경우, 그 문장을 지우는 기능
View string_replace_util.py
import re
class StringReplaceUtil(object):
"""
코퍼스와 같은 말뭉치에서 정해진 단위로 문장을 나누고, 한 문장에서 특정한 패턴이 있을 경우, 그 문장을 지우는 기능
"""
def __init__(self, text: str, token_pattern: str):
"""