Texts from twitter has been collected to decide the impact, it has been causing the public .We took a testing dataset and used neural network – Model training for testing the retrieved tweets and gain prediction of the sentiments from their tweets.

Generate an AI market research report

Make AI model detected Fake NEWS

This a project which predicts the stock price of Tesla for a given time period & based upon the previous 10 years of historical data. Here, numerical and sentimental analysis is performed with the help of natural language toolkit (NLKT), Textblob, sklearn etc. By observing the previous trends of the market stock price and sentiments of the news …

👱🏻‍♀️ My lovely italian chatbot and personal assistant

This repositories contains all the materials and the supports used to perform a Sentiment Analysis Classification on Twitter's tweets. This project was part of a competion of the Data Science Lab course - Politecnico di Torino.

Using Machine Learning user can enter tv show or movie description to predict that description’s rating & OMDB genre

Performance a Pipelines, grid search and text mining. Let's start with several basic exercises.

DS Practice

A sentimental analysis of data from Twitter regarding customer sentiment for 6 US airlines: American, Delta, Southwest Airlines, United, US Airways, and Virgin America. Then use Tensor Flow to predict the chance of a tweet to be positive, negative, or neutral.

Emotions Analysis

NLP Sentiment Analysis Document Scoring Method

In this repository I explained the basics of Natural Language Toolkit.

Scripts used to solve exercises in Data Science course with Python.

Project for the University Master Degree Course of Information Retrieval

Series of experiment sessions using NLP, Google Cloud Vision and AWS