Karthik Ravi kaddynator

## overview.json
{
  "embeddings": [
    {
      "tensorName": "My tensor",
      "tensorShape": [
        1000,
        50
      ],
      "tensorPath": "https://www.dropbox.com/s/f10xrzxnwi1fz85/overview_tensor.tsv?dl=1",
      "metadataPath": "https://www.dropbox.com/s/nrd66qyx0oiic1k/overview_metadata.tsv?dl=1"

## w2v_visualizer.py
# encoding: utf-8
"""
@author: BrikerMan
@contact: eliyar917@gmail.com
@blog: https://eliyar.biz
@version: 1.0
@license: Apache Licence
@file: w2v_visualizer.py
@time: 2017/7/30 上午9:37
"""

## awesome-kge.md

      
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                Awesome Knowledge Graph Embedding Approaches
              
          
    Awesome Knowledge Graph Embedding Approaches


This list contains repositories of libraries and approaches for knowledge graph embeddings, which are vector representations of entities and relations in a multi-relational directed labelled graph. Licensed under CC0.
Libraries


🆕 AmpliGraph (4 algorithms) @ https://github.com/Accenture/AmpliGraph
Embedding framework (5 algorithms) @ https://github.com/BookmanHan/Embedding


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                Hackathons
              
          
## aboutme.gif

      
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                About_Me
              
          
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                social_media
              
          
## travel.gif

      
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                My Travel
              
          
## DFM.R
library(readr)
library(slam)
library(quanteda);
library(tidyverse);
library(RColorBrewer)

###--------------------creating document term matrix
##remove stopwords,  punctuation, symbols,
##the TEXTINPUT is the input text for the dfm
dfm <- dfm(TEXTINPUT,

## Making to_csv and read_csv consistent for pandas
# This works in MACs
# Dataframe can also be used in R

import pandas as pd

##reading a csv file
df = pd.read_csv("PATH WHERE YOUR FILE IS SAVED/filename.csv", encoding='utf-8',lineterminator = '\n',index_col=0)

##writing a csv file
df.to_csv("PATH WHERE YOU WANT TO SAVE YOUR FILE/filename.csv",quoting=csv.QUOTE_NONNUMERIC, date_format='%Y-%m-%d %H:%M:%S', encoding='utf-8',line_terminator = '\n')
	{
	"embeddings": [
	{
	"tensorName": "My tensor",
	"tensorShape": [
	1000,
	50
	],
	"tensorPath": "https://www.dropbox.com/s/f10xrzxnwi1fz85/overview_tensor.tsv?dl=1",
	"metadataPath": "https://www.dropbox.com/s/nrd66qyx0oiic1k/overview_metadata.tsv?dl=1"
	# encoding: utf-8
	"""
	@author: BrikerMan
	@contact: eliyar917@gmail.com
	@blog: https://eliyar.biz
	@version: 1.0
	@license: Apache Licence
	@file: w2v_visualizer.py
	@time: 2017/7/30 上午9:37
	"""
	library(readr)
	library(slam)
	library(quanteda);
	library(tidyverse);
	library(RColorBrewer)

	###--------------------creating document term matrix
	##remove stopwords, punctuation, symbols,
	##the TEXTINPUT is the input text for the dfm
	dfm <- dfm(TEXTINPUT,
	# This works in MACs
	# Dataframe can also be used in R

	import pandas as pd

	##reading a csv file
	df = pd.read_csv("PATH WHERE YOUR FILE IS SAVED/filename.csv", encoding='utf-8',lineterminator = '\n',index_col=0)

	##writing a csv file
	df.to_csv("PATH WHERE YOU WANT TO SAVE YOUR FILE/filename.csv",quoting=csv.QUOTE_NONNUMERIC, date_format='%Y-%m-%d %H:%M:%S', encoding='utf-8',line_terminator = '\n')