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Rahul Indra's Projects

add-cover-art icon add-cover-art

Change cover photo of all your songs automatically using python

algorithms icon algorithms

A Repository to store implementation of some of the famous Data Structures and Algorithms (mainly in C/C++/Java/Python) for everyone to learn and contribute.

amazonfoodreviews icon amazonfoodreviews

Amazon Fine Food Reviews Analysis Data Source: https://www.kaggle.com/snap/amazon-fine-food-reviews 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: 1.Id 2 ProductId - unique identifier for the product 3 UserId - unqiue identifier for the user 4 ProfileName 5 HelpfulnessNumerator - number of users who found the review helpful 6 HelpfulnessDenominator - number of users who indicated whether they found the review helpful or not 7 Score - rating between 1 and 5 8 Time - timestamp for the review 9 Summary - brief summary of the review 10 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 the Score/Rating. A rating of 4 or 5 could be cosnidered a positive review. A review of 1 or 2 could be considered negative. A review of 3 is nuetral and ignored. This is an approximate and proxy way of determining the polarity (positivity/negativity) of a review.

apollo-11 icon apollo-11

Original Apollo 11 Guidance Computer (AGC) source code for the command and lunar modules.

cadence icon cadence

Cadence is a distributed, scalable, durable, and highly available orchestration engine to execute asynchronous long-running business logic in a scalable and resilient way.

caffe icon caffe

Caffe: a fast open framework for deep learning.

crimedetection icon crimedetection

It is a multi-label classification problem Multi-label Classification: Multilabel classification assigns to each sample a set of target labels. This can be thought as predicting properties of a data-point that are not mutually exclusive, such as topics that are relevant for a document.There are crime charges(labels) for every article description in the dataset. Our tasks is find crime charges for future descriptions. Credit: http://scikit-learn.org/stable/modules/multiclass.html

deedy-resume icon deedy-resume

A one page , two asymmetric column resume template in XeTeX that caters to an undergraduate Computer Science student

desktop icon desktop

Mattermost Desktop application for Windows, Mac and Linux

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