Simran Nagpurkar's Projects
Amazon Fine Food Reviews Analysis Data Source: https://www.kaggle.com/snap/amazon-fine-food-reviews EDA: https://nycdatascience.com/blog/student-works/amazon-fine-foods-visualization/ The Amazon Fine Food Reviews dataset consists of reviews of fine foods from Amazon. 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 Attribute Information: Id ProductId - unique identifier for the product UserId - unqiue identifier for the user ProfileName HelpfulnessNumerator - number of users who found the review helpful HelpfulnessDenominator - number of users who indicated whether they found the review helpful or not Score - rating between 1 and 5 Time - timestamp for the review Summary - brief summary of the review Text - text of the review Objective: Given a review, determine whether the review is positive (rating of 4 or 5) or negative (rating of 1 or 2). [Q] How to determine if a review is positive or negative? [Ans] We could use Score/Rating. A rating of 4 or 5 can be cosnidered as a positive review. A rating of 1 or 2 can be considered as negative one. A review of rating 3 is considered nuetral and such reviews are ignored from our analysis. This is an approximate and proxy way of determining the polarity (positivity/negativity) of a review.
Desigining Advanced Data Architectures for Business Intelligence.
Advances Data Science
Desigining Advanced Data Architectures for Business Intelligence.
Tableau Dashboard
Desigining Advanced Data Architectures for Business Intelligence.
Advances Data Science
Machine Learning & Python in Finance
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent