aiyazsarwar Goto Github PK

100-pandas-puzzles

100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)

amazon-apparel-recommendation

amazon-fine-food-reviews

Kaggle DataSet

amazon-fine-food-reviews-aaic

amazon-fine-food-reviews-analysis_knn

KNN on Amazon Fine Food Reviews Analysis

amazon-fine-food-reviews-analysis_logistic-regression

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.

amazon-food-reviews-rf

Application of Random Forest and XGBOOST on Amazon Food Reviews Dataset

amazon-food-reviews-svm

Amazon-Food-Reviews-SVM

clustering-methods-on-amazon-reviews-text-data

Clustering methods on Amazon reviews text data

data-analysis-and-machine-learning-projects

Repository of teaching materials, code, and data for my data analysis and machine learning projects.

decision-tree

Amazon Fine Food Reviews Analysis_Decision Trees

deep-learning

Contains Deep learning projects

deploying-machine-learning-models

Example Repo for the Udemy Course "Deployment of Machine Learning Models"

deploying-ml-models

ds_salary_proj

Repo for the data science salary prediction of the Data Science Project From Scratch video on my youtube

exercises_

expert-guide

facebook-friend-recommendation

flask_heroku

Deploying Flask App to Heroku

herokudemo

knearestneighbour

Amazon Fine Food Reviews

knearestneighbours

KNearestNeighbours on Amazon food reviews text data

machinelearning

Machine learning for beginner(Data Science enthusiast)

personalized-cancer-diagnosis

quora-question-pair-similarity

stack-overflow-tag-prediction

taxi-demand-prediction-in-new-york-city

Time-series forecasting and Regression - To find number of pickups, given location cordinates(latitude and longitude) and time, in the query reigion and surrounding regions. To solve the above we would be using data collected in Jan - Mar 2015 to predict the pickups in Jan - Mar 2016.

testautomation

testing and auto build for docker

yellow-taxi-prediction

To find number of pickups, given location cordinates(latitude and longitude) and time, in the query reigion and surrounding regions.