Vibhansh Lord-V15

## img generation from text.ipynb

      
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                Lord-V15
                / img generation from text.ipynb
            
            
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              March 28, 2024 05:03
            
              
                Prompt based image generation using Stable diffusion with MLX
              
          
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## S3-knowledge-graph.html
<html>
    <head>
        <meta charset="utf-8">

            <script src="lib/bindings/utils.js"></script>
            <link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/dist/vis-network.min.css" integrity="sha512-WgxfT5LWjfszlPHXRmBWHkV2eceiWTOBvrKCNbdgDYTHrT2AeLCGbF4sZlZw3UMN3WtL0tGUoIAKsu8mllg/XA==" crossorigin="anonymous" referrerpolicy="no-referrer" />
            <script src="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/vis-network.min.js" integrity="sha512-LnvoEWDFrqGHlHmDD2101OrLcbsfkrzoSpvtSQtxK3RMnRV0eOkhhBN2dXHKRrUU8p2DGRTk35n4O8nWSVe1mQ==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>


<center>

## scatter-plot.markdown

      
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                Lord-V15
                / scatter-plot.markdown
            
            
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              June 6, 2023 12:55
            
              
                Train vs Test data chart
              
          
    Scatter plot


A Pen by Vibhansh on CodePen.
License.

  
## Text Dependent Recognition.ipynb

      
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                Lord-V15
                / Text Dependent Recognition.ipynb
            
            
              Created
              April 8, 2022 13:18
            
              
                Azure Cognitive - Speech Recognition Python
              
          
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## FastAPI-DetaBase.py
# all of the login functionality was handled by AWS Cognito.
# lib imports
from fastapi import APIRouter, HTTPException, status
from pydantic import BaseModel
from typing import Optional
from deta import Deta
import os
from dotenv import load_dotenv

# .env file loading

## verification.html
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
  <meta name="viewport" content="width=device-width, initial-scale=1.0" />
  <meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />
  <title>Verify your email address</title>
  <style type="text/css" rel="stylesheet" media="all">
    /* Base ------------------------------ */
    *:not(br):not(tr):not(html) {
      font-family: Arial, 'Helvetica Neue', Helvetica, sans-serif;

## SpeakerRecognition.md

      
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                Lord-V15
                / SpeakerRecognition.md
            
            
              Last active
              September 12, 2023 01:56
            
              
                MICROSOFT AZURE SPEAKER RECOGNITION IN PYTHON 
              
          
    For anyone in the future who's gonna try this service from Azure, let me give you an easy way out. I spent a lot of time on Speaker Recognition and the official docs say something and the samples given do something else.
I will use the official REST API Docs for the text-independent method.
CREATE PROFILE 👇
import http.client
import json

conn = http.client.HTTPSConnection('westus.api.cognitive.microsoft.com')


## nlp-engineer-_-technical-selection-round.ipynb

      
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                Lord-V15
                / nlp-engineer-_-technical-selection-round.ipynb
            
            
              Last active
              July 2, 2021 13:44
            
              
                NLP Engineer - VIBHANSH
              
          
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## stylometry_pystyl.py
# 2-D Scatter Plot using PCA
from pystyl.analysis import distance_matrix, hierarchical_clustering

from pystyl.visualization import scatterplot, scatterplot_3d

from pystyl.analysis import pca

pca_coor, pca_loadings = pca(corpus, nb_dimensions=2)

scatterplot(corpus, coor=pca_coor, nb_clusters=0, loadings=pca_loadings, plot_type='static',\

## kNN_ES_search.py
# Idea : use this to index Quora's Question Pair dataset and explore the search results
doc = {
    "settings": {
        "index.knn": True
    },
    "mappings": {
        "properties": {
            "title": {
                "type" : "text"
            },
	<html>
	<head>
	<meta charset="utf-8">

	<script src="lib/bindings/utils.js"></script>
	<link rel="stylesheet" href="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/dist/vis-network.min.css" integrity="sha512-WgxfT5LWjfszlPHXRmBWHkV2eceiWTOBvrKCNbdgDYTHrT2AeLCGbF4sZlZw3UMN3WtL0tGUoIAKsu8mllg/XA==" crossorigin="anonymous" referrerpolicy="no-referrer" />
	<script src="https://cdnjs.cloudflare.com/ajax/libs/vis-network/9.1.2/dist/vis-network.min.js" integrity="sha512-LnvoEWDFrqGHlHmDD2101OrLcbsfkrzoSpvtSQtxK3RMnRV0eOkhhBN2dXHKRrUU8p2DGRTk35n4O8nWSVe1mQ==" crossorigin="anonymous" referrerpolicy="no-referrer"></script>


	<center>
	# all of the login functionality was handled by AWS Cognito.
	# lib imports
	from fastapi import APIRouter, HTTPException, status
	from pydantic import BaseModel
	from typing import Optional
	from deta import Deta
	import os
	from dotenv import load_dotenv

	# .env file loading
	<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
	<html xmlns="http://www.w3.org/1999/xhtml">
	<head>
	<meta name="viewport" content="width=device-width, initial-scale=1.0" />
	<meta http-equiv="Content-Type" content="text/html; charset=UTF-8" />
	<title>Verify your email address</title>
	<style type="text/css" rel="stylesheet" media="all">
	/* Base ------------------------------ */
	*:not(br):not(tr):not(html) {
	font-family: Arial, 'Helvetica Neue', Helvetica, sans-serif;
	# 2-D Scatter Plot using PCA
	from pystyl.analysis import distance_matrix, hierarchical_clustering

	from pystyl.visualization import scatterplot, scatterplot_3d

	from pystyl.analysis import pca

	pca_coor, pca_loadings = pca(corpus, nb_dimensions=2)

	scatterplot(corpus, coor=pca_coor, nb_clusters=0, loadings=pca_loadings, plot_type='static',\
	# Idea : use this to index Quora's Question Pair dataset and explore the search results
	doc = {
	"settings": {
	"index.knn": True
	},
	"mappings": {
	"properties": {
	"title": {
	"type" : "text"
	},