This repository contains data analytics projects that are important to our day to day Machine learning activities

It is a machine learning project compatible to provide a tentative price of laptop according to the user configurations. It needs lots of feature engineering, and pre- processing and at last Random Forest gave the best accuracy of 0.8837.

Amazon Reviews Analysis

Sentiment Analysis of Amazon Reviews of a product using Vader Lexicon. Extracting positive/negative/neutral reviews.

This notebook will show you how to implement a deep leaning algorithm (LSTM) on the Amazon Alexa Reviews dataset

Sentiment Analysis on Amazon Review using Deep Learning

The objective of this project is to discover insights into consumer reviews.

Aspect-based sentiment analysis on Amazon reviews

A model that predicts the sentiment for a given Amazon review. This is a Naive Bayes model that utilizes NLP for pre-processing.

Amazon Reviews Sentiment Classifications and Textual Similarities with Universal Sentence Encoder.

This project focuses on sentiment analysis of Amazon product reviews using machine learning and natural language processing techniques. 💬🔍📈

Sentiment Analysis on Whirl Pool Washing Machine Based on its reviews from Amazon Website

This repository showcases the outcomes of an Exploratory Data Analysis (EDA), including visualisation, conducted on the comprehensive Amazon Review Data (2018) dataset, consisting of nearly 233.1 million records and occupying approximately 128 gigabytes (GB) of data storage, using MongoDB and PySpark.

Sentiment analysis lets you analyze the sentiment behind a given piece of text. In this notebook, we have done sentimental analysis for amazon shoe reviews, using 2 RNN models(LSTM and GRU)

Collection of university projects exams

This repository contains the results of my simple sentiment analysis of Amazon Reviews.

Text classification with Hugging Face Transformers on Multilingual Amazon Reviews dataset

- Sentiment Analysis classifier of amazon customer reviews

Big Data Homework

Amazon Review Scraper for hassle-free review data extraction, including authors, titles, descriptions, ratings, dates, and more.