This repository contains some data science portfolio projects for academic, self-improvement and hobby purposes. Projects are prepared in iPyhon Notebook format.
Note: Data used in the projects is for demonstration purposes only.
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- Generate TV Script with RNN: A model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.
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Predicting Boston Housing Prices: A model to predict the value of a given house in the Boston real estate market using various statistical analysis tools. Identified the best price that a client can sell their house utilizing machine learning.
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Predicting Advertisement: In this project we will be working with a fake advertising data set, indicating whether or not a particular internet user clicked on an Advertisement. We will try to create a model that will predict whether or not they will click on an ad based off the features of that user.
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Lending Club: For this project we will be exploring publicly available data from LendingClub.com. Lending Club connects people who need money (borrowers) with people who have money (investors).
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Iris Flower: In this project we will use the support vector machine method in examining the famous iris data set.
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Clustering Universities: For this project we will attempt to use KMeans Clustering to cluster Universities into to two groups, Private and Public.
Tools: scikit-learn, Pandas, Numpy, Seaborn, Matplotlib
- Classify Yelp Reviews: In this NLP project we will be attempting to classify Yelp Reviews into 1 star or 5 star categories based off the text content in the reviews.
Tools: NLTK, scikit-learn, Pandas, Numpy, Seaborn, Matplotlib
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