TowardsMachineLearning

NLP

Build WhatsApp chatbot using NodeJS – part4

Step 13. Handle user’s input:- So here we’ve created another folder called “pdf” and inside that we’ve created another file called Index.js in which we’ve written this function called ” getQuotation ” to transform data as per our needs. Step 14. Create invoice Here we’ll be writing createInvoice.js file inside pdf folder and we’ll using …

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Build WhatsApp chatbot using NodeJS – part2

Introduction:- In this post we’ll solve POC in which “MachineLearning-made-easy.com” wishes to use WhatsApp Bot to generate invoices for its client. WhatsApp Bot should also be able to send these invoices to respective clients. So stay tuned to check this project in my next post. Step 1. Creating an agent on Dialogflow:- Create a new …

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Build WhatsApp chatbot using NodeJS – part1

Introduction:- WhatsApp has massive userbase of over 1.5 Billion people. That’s one of main reasons why Businesses had keen eye on WhatsApp. Until now small business have managed creating WhatsApp groups and putting manpower on the job of communicating or sharing offers ,deals or other types of customers connect initiatives. But as you can see …

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Introduction to Natural Language Processing -Part 2

Step1. Load all necessary libraries and remove previously stored data from R-Studio rm(list = ls()) #Remove data from previous session in R-Studio #Load all libraries and dependencies load_libry<- function(x){ for(i in x){ if(! require(i,character.only = TRUE)){ install.packages(i,dependencies = TRUE) } } } pkgs <- c(“dplyr”,”tidyverse”,”tidytext”,”tm”,”SnowballC”,”reshape2″,”e1071″,”tm”,”caret”,”textstem”, “doSNOW”,”parallel”,”randomForest”,”janeaustenr”,”readxl”,”rlist”,”tokenizers”,”stopwords”, “wordcloud2″,”wordcloud”,”doParallel”,”parallel”) load_libry(pkgs) #set working directory setwd(“D:/Praveen/MachineLearning”) Step2. Load data …

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Introduction to Natural Language Processing-Part 1

What is Natural Language Processing? Natural language refers to the way we, humans, communicate with each other namely, speech and text.We are surrounded by text.Think about how much text you see each day: Signs,Menus,Email,SMS,Web Pages,logs,chat messages ,and so much more…The list is endless. And this is where Natural Language processing comes in picture. The study …

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