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Sahil Patni's Projects

analyze-a-b-test-eda icon analyze-a-b-test-eda

This project will assure you have mastered the subjects covered in the statistics lessons. The hope is to have this project be as comprehensive of these topics as possible.

disaster_respone_project icon disaster_respone_project

Better classification of responses can help in faster aid and rescue. An efficient and user friendly app can be very crucial at these times.

exploring-weather-trends-sql icon exploring-weather-trends-sql

In this project, you will analyze local and global temperature data and compare the temperature trends where you live to overall global temperature trends.

ford-gobike-system-eda icon ford-gobike-system-eda

Ford GoBike System Dataset is a dataset that contains trip data from Lyft's bike service for public use. Variables include trip duration, start time, end time with date, start station and end station names, start and end coordinates, and customer type.

generate-tv-scripts-nlp-project icon generate-tv-scripts-nlp-project

you'll generate your own Seinfeld TV scripts using RNNs. You'll be using part of the Seinfeld dataset of scripts from 9 seasons. The Neural Network you'll build will generate a new ,"fake" TV script, based on patterns it recognizes in this training data.

investigate-tmdb-movie-dataset-eda icon investigate-tmdb-movie-dataset-eda

I choose the TMDb movie data set for data analysis. This data set contains information about 10,000 movies collected from The Movie Database (TMDb), including user ratings and revenue.I would like to find other intresting patterns in the dataset.

loan-data-from-prosper-eda icon loan-data-from-prosper-eda

This data set contains 113,937 loans with 81 variables on each loan, including loan amount, borrower rate (or interest rate), current loan status, borrower income, and many others.

recommendations-system-ibm icon recommendations-system-ibm

Analyze user behavior and social network data on the IBM Watson platform to build a recommendation engine based on surface content most likely to be relevant to a user

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