paul-jm

Pinned Repositories

Auckland_Housing
Scraped 500 listings from myrent.co.nz, in order to geo-locate the most attractive rooms available on Google maps.
Language:Jupyter Notebook00
BerlinHousing
Scraped data from https://www.immobilienscout24.de/, used Google Maps API plus folium to make an interactive plot of listings across Berlin.
Language:HTML00
BI-Project
00
Bike_Sharing_with_Dask
Language:Jupyter Notebook00
DataViz_FinalProject
Visualization of AirBNB accommodation options in Amsterdam using R
Language:R00
Fake_News_Detection_NLP
Language:Jupyter Notebook0 0 00
Forecasting_time_series_r
Forecasting time series assignment for Coca Cola earnings comparing various SARIMA models, carried out in R.
Language:R00
Heart_Rate_for_Wearable
Language:Python00
House_Prices
Language:R00

paul-jm's Repositories

paul-jm/Auckland_Housing
Scraped 500 listings from myrent.co.nz, in order to geo-locate the most attractive rooms available on Google maps.
Language:Jupyter Notebook00
paul-jm/BerlinHousing
Scraped data from https://www.immobilienscout24.de/, used Google Maps API plus folium to make an interactive plot of listings across Berlin.
Language:HTML00
paul-jm/BI-Project
00
paul-jm/Bike_Sharing_with_Dask
Language:Jupyter Notebook00
paul-jm/DataViz_FinalProject
Visualization of AirBNB accommodation options in Amsterdam using R
Language:R00
paul-jm/Fake_News_Detection_NLP
Language:Jupyter Notebook0 0 00
paul-jm/Forecasting_time_series_r
Forecasting time series assignment for Coca Cola earnings comparing various SARIMA models, carried out in R.
Language:R00
paul-jm/Heart_Rate_for_Wearable
Language:Python00
paul-jm/House_Prices
Language:R00
paul-jm/ie-mbd-advanced-python
"Advanced Python" subject from the Master in Big Data @ IE
Language:Jupyter Notebook
paul-jm/kickstarter_campaigns
Forecasting Campaign Success
Language:Jupyter Notebook
paul-jm/Machine_Learning_II_Employee_Churn
Employee churn prediction model in Python
Language:Jupyter Notebook
paul-jm/Madrid_Pollution_Analysis_R
Analysis of hourly pollution data across 20+ stations in Madrid for several pollutants, carried out in R
paul-jm/mbd-bidw
Business Intelligence and Data Warehousing
paul-jm/NLP-Text_Summarization
Datasets and Individual Text Files for Text Summarization
Language:HTML
paul-jm/Pump_it_up_challenge
Developed a machine learning algorithm taking part in Kaggle's pump it up challenge to predict state of wells in Tanzania, carried out in Python
Language:Jupyter Notebook
paul-jm/Python_triangles
Python script that creates triangular numbers, tetrahedral numbers, binomial coefficients, and pascal's triangles
Language:Jupyter Notebook
paul-jm/SocialNetworkAnalysis_Final
Algorithm to predict most desirable itineraries from A to B for various U.S. Airlines networks in R
Language:HTML0 0
paul-jm/Stocks_Cluster_Analysis_R
Clustering analysis of various stocks in R