Leana Critchell's repositories
king_county_housing_prices_linear_regression
This repo contains EDA of 2019 King County housing data. It also contains iterations of generating linear regression models to predict home sale prices.
Rate-5-Get-5-Movie-Recommendation-System
We aim to create a recommendation system based on the MovieLens dataset from the GroupLens research lab at the University of Minnesota. Furthermore, we would like to deploy a web app that will alloy a user to enter some ratings for movies that they have seen, and then, based on the model we have implemented, it will reccomend movies that align with their interests.
Cene-Image-Classification
Cene is an image classification application that aims to classify images of 6 landscapes into corresponding albums. The landscapes this app is capable of classifying are buildings, forests, glaciers, mountains, seas and streets.
nationalism_using_gdelt
This project aims to dive deeper into extracting the data in the GDELT Project which is a 'global database of society'. More specifically, I aim to investigate nationalistic movements around the world through NLP practices as well as investigating trends over time using time series analysis.
respones_to_resistance_model_analysis
This project analyses response to resistance data for the Dallas police municipality. A model is created to predict whether citizens are injured if they resist police arrest.
credit-card-fraud-detection
This dataset and problem, a provided by Kaggle, can be found here: https://www.kaggle.com/mlg-ulb/creditcardfraud. The aim is to identify fraudulent credit card transactions as well as to deal with the significant class imbalance issues present in this dataset.
customer_churn_prediction_syriatel
This project aims to provide SyriaTel with a model to help predict whether a customer will soon churn.
opportunity_youth_statistical_analysis
This project offers an updated estimate of the number of Opportunity Youth in South King County using the 2017 5-year American Community Survey (ACS) Public Use Microdata Survey (PUMS).
Coding-in-TensorFlow
Nothing strengthens better your knowledge in Deep Learning than coding an actual model and application. Take the 5 week challenge with Robert, David and George and join us each Friday for a fun and engaging hands-on coding session using TensorFlow 🎉
dask-tutorial
Dask tutorial
getting-up-to-speed-with-dask
Gentle introduction to Dask
madrid_temperature_time_series
This project aims to investigate the Madrid Temperature dataset and identify the best ML framework that minimizes the mean absolute error.