In this three-part series, we will teach you everything you need to build and deploy your own Chatbot. This is the first part of the series, where the rest of the series will cover the following topics:
- Part 0: Project introduction and overview.
- Part 1: Building a content-based recommender using a cosine similarity algorithm.
- Part 2: Deploying the model on AWS serverless computing platform and creating an interactive chatbot web application.
- Part 3: Model analysis and future recommendations.
We use a Jupyter Python 3 notebook as a collaborative coding environment for this project, and other bits of code for the…
Introduction
This tutorial makes use of 3 cleaned data sets, as discussed and prepared in part 1 of this series.
- Dimension reduced sentiment data of 1,600,000 tweets labelled 0 for negative and 1 for positive sentiment.
- 8,981 unseen tweets about covid-19.
- Dimension reduced version of the 8,981 covid-19 tweets.
The goal is to train a LDA model on the sentiment data and use that model to predict the sentiment of each covid-19 tweet.
The code accompanying this tutorial can be found here: https://github.com/aletna/Covid-19-Tweets-Classification.git
We will be using the following libraries:
import numpy as np
from sklearn.model_selection import train_test_split
from sklearn import metrics
import pandas…
