Skip to content

Implementation of Machine learning algorithms KNN, Naive Bayes, Logistic Regression, SGD for linear regression, SVM, Decision Trees,Random Forest,k means and Truncated SVD on Amazon fine food reviews data set

Notifications You must be signed in to change notification settings

pavankumargoli/Machine-learning-Algorithms-on-Amazon-Fine-Food-Reviews-Analysis

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

11 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Amazon Fine Food Reviews Analysis

The Amazon Fine Food Reviews dataset consists of reviews of fine foods from Amazon.

This dataset consists of reviews of fine foods from amazon. The data span a period of more than 10 years, including all ~500,000 reviews up to October 2012. Reviews include product and user information, ratings, and a plain text review. It also includes reviews from all other Amazon categories.

Data Source : https://www.kaggle.com/snap/amazon-fine-food-reviews

Number of reviews: 568,454
Number of users: 256,059
Number of products: 74,258
Timespan: Oct 1999 - Oct 2012
Number of Attributes/Columns in data: 10

Objective

This project is focused to find the best model which can classify the class labels with high accuracy and less test error. Here the source dataset consists of reviews of fine foods from amazon(kaggle).

Will implement varioud Machine learning models on this data

About

Implementation of Machine learning algorithms KNN, Naive Bayes, Logistic Regression, SGD for linear regression, SVM, Decision Trees,Random Forest,k means and Truncated SVD on Amazon fine food reviews data set

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published