Monday, November 29Digital Marketing Journals

projects

How to build a chatbot using Rasa and Python | by Arya Pandey | Sep, 2021
ai, ai bot, ai chat, ai chatbot, best chatbot, chatbot, chatbot ai, chatbot app, chatbot online, chatbot website, chatbots, conversation with ai, creating chatbots, projects, python, rasa, robot chat

How to build a chatbot using Rasa and Python | by Arya Pandey | Sep, 2021

Today we’ll be talking about how to make an AI-powered chatbot using Rasa and Python. It doesn’t matter if you have deep knowledge of python or are just a beginner in the world of coding!This article mainly focuses on the AI framework, Rasa, and a little bit of python. Before getting started, let me tell you the required software to be installed for the project.Visual Studio 2019 C++ Build ToolsAnaconda (Conda Package)I am assuming that you already have Python 3.8 installed in your PC since Python 3.9 version doesn’t work with rasa, it has some issue so I’ll suggest you download version 3.8 if you don’t have it. Here’s the link: https://www.python.org/downloads/. Thank me later :PYou can download the following two softwares from the link provided below (if you don’t already have them on...
Natural Language Processing (NLP) | Chatbots Life
ai bot, ai chat, ai chatbot, best chatbot, chatbot, chatbot ai, chatbot app, chatbot online, chatbot website, conversation with ai, creating chatbots, machine-learning, natural, nlp, projects, python-programming, robot chat

Natural Language Processing (NLP) | Chatbots Life

What is Natural Language Processing?NLP is a method or a way in which computer interprets the Human language are perform the task. Alexa, Siri, etc. are some of its example.Let’s start with the Spam Classifier:The spam classifier predicts whether received message is a ham or a spam.Let’s start with the dataset: The dataset consists of 5572 messages and their labels which is either “ham” or “spam”.import pandas as pdmessages = pd.read_csv(“SMSSpamClassifier”,sep=”t”,names=[‘label’,’message’])Now the labels needs to be converted in 0 and 1 labels which can be done using get_dummies() method of pandas library.y = pd.getdummies(messages[‘labels’])y = y.iloc[:1].valuesHere, y wil contain 0 for “ham” labels and 1 for “spam” labels.Now let’s look at independent data i.e. for x. For that 1st we...