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Greg Bhola's Projects

big_data icon big_data

This is a Big Data project using AWS, pyspark-sql, pyspark and Google Collaboratory to determine if there is any bias in the reviews of vine and non-vine reviewers on Amazon.

credit_risk icon credit_risk

Performed supervised machine learning using oversampling, undersampling and combination sampling techniques to determine credit risk for bank customers.

cryptocurrencies icon cryptocurrencies

Analyzing the performance of Cryptocurrencies using Unsupervised Machine Learning methods such as Principal Component Analysis (PCA) and KMeans Clustering. Data visualizations were executed using HVplot and PowerBI.

election_analysis icon election_analysis

Using Python to audit election results. In this project, I practiced the basics of for loops and conditionals with logical operators. There was also scope to refactor code.

mapping_earthquakes icon mapping_earthquakes

Mapbox and Leaflet maps were created to display the most recent earthquakes over the past 7 days.

mission-to-mars icon mission-to-mars

Created a web app using Flask to display web data. MongoDB was also used to store data from web scrape.

movies-etl icon movies-etl

An ETL process for a movies database from Wikipedia and Kaggle. Demonstrated the use of Pandas, RegEx, functions and try-except blocks to create an automated ETL pipeline.

neural_networks icon neural_networks

Learning to build my own machine learning model using TensorFlow to predict the success of a venture.

pyber_analysis icon pyber_analysis

Jupyter Notebook project using Pandas & Matplotlib to visualize and examine the dataset of a mock ride-sharing business operating in urban, suburban, and rural areas. Merge, groupby, sums, count, pivot table methods utilized. Bubble charts, boxplots, pie charts, and line charts created.

school_district_analysis icon school_district_analysis

This is a project that I did to solidify some of my basic ETL skills in Python. Some of the methods used include Merge, Filter, CLice, Sort, Count and GroupBy.

surfs_up icon surfs_up

Creating an app to monitor weather data for a potential surfboard and milkshake start-up.

titanic_exploratory_analysis icon titanic_exploratory_analysis

In this project, I used r programming to perform ETL and construct a Logistic Regression model to predict which passengers survived the sinking of the Titanic.

ufos icon ufos

Created an HTML base page that included an interactive Javascript dynamic table.

us_election_nlp icon us_election_nlp

This was my first NLP team project. We used Twint to scrape Twitter information and used this data to perform Sentiment/Emotion Analysis for the Presidential candidates in the last four elections. Other key resources such as TextBlob, NLTK, MongoDB and Python were also used to complete this analysis.

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