Leveraging 21,000+ Amazon Reviews to conduct Natural Language Processing (NLP), Sentiment Analysis & Supervised Machine Learning to select the best specialty ice cream flavor for our expansion.

Dockerized pipeline that collects tweets from Twitter related to a chosen topic and stores them in MongoDB, analyzes the sentiment of each tweet, loads analyzed tweets in a PostgresDB and posts tweets with sentiment score binned as positive, neutral or negative to a slack channel.

Currently learning NLP

[NLP, VADER] Project 3 for General Assembly's Data Science Immersive Course. This project builds on the VADER model to create a sentiment analysis model for YouTube comments.

Sentiment analysis on three different datasets using Lexicon and Rule-based sentiment analysis tools

A python script Vader analysis of tweets based on the key word " World Cup 2018"

POS, NER, Sentiment & Semantics, VADER, LDA, Topic Modeling using spaCy and NLTK

Review Network Vizualization

Krishi Mart (farmer's portal) - an academic project built with ReactJS. Authentication and storage is implemented using Firebase. The review system is enhanced by using Vader Sentimental Analysis library, to display most appreciated products to the users.

This is the Final Year Project based on Machine Learning Concepts. This project was developed to analyze the sentiments of a given statement.

In this repository I will be doing some sentiment analysis in python using two different techniques: VADER (Valence Aware Dictionary and sEntiment Reasoner) - Bag of words approach Roberta pre-trained Model from Huggingface Pipeline

Analyze your text on a positive, neutral or negative (Sentiment analysis)

Twitter Analysis from UK 2019 election tweets.

A simple web app to classify the sentiment of a person conveyed through speech as positive, negative or neutral through a machine learning approach.

Sentiment analysis

Yummy: A Recipe Reviews Sentiment Analysis

Geographical Networks Project 2020-2021. Given the current situation, from the pandemic phenomenon of Covid-19, we want to carry out a project based on Sentiment Analysis through Twitter, to understand what the Italian population thinks about it, focusing on how it reacted following the various decisions governmental (dpcm, etc.).

This project implements a data pipeline using Docker to extract, transform (sentiment analysis) and load twitter posts and finally post them on Slack.