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14d001_spatial_cv

Cross-Validation for Model Assessment and Model Selection with Geospatial Data 🌍📈

14d002_programming_projects

In this project, we analyse two algorithms, the Edit distance to calculate the least number of edit operations that are necessary to modify one string into another and Huffman codes to construct the optimal prefix code given input text.

14d004_computing_assignment

14D004 Computing Assignment: EDA of Traffic Accidents in the United Kingdom Between 2005-2015 🚗

14d004_scraping_project

14D004 Scraping Project: Scrape all the available courses on datacamp.com and scape all job posts on jobsinbarcelona.es using scrapy

15d019_exercise

Basic Demand Estimation Exercise - Estimating the demand elasticities of Kraft and Hellman's mayonnaise in the broader Chicago market

15d019_final_project

15D019 Final Project: When it Hurts: demand estimation in the market for over the counter (OTC) analgesics using a nested logit model.

agribrain

AgriBrain is an agriculture and irrigation management system that integrates monitoring, analysis and automation into a single platform

aws_dashboard_deployment

Blog post: Steps to deploy a flexdashboard or shiny app using AWS and R-Shiny and RStudio Servers

balena-sense-hat-python-starter

A starter project with Python3 and Sense-HAT library ready to go

computing-brushup-exam

customer_churn

The goal is to estimate users’ long-term (30 days later) engagement (engaged vs churned) with the news site based on their interactions with the site in the short term.

kiwibot

Building a flight search chatbot from scratch using RASA ✈️

landcover_classification

Determine land use and land cover classification based on Sentinel-2 satellite images with state-of-the-art performance 🛰

landcover_segmentation

Automatic categorization and segmentation of land cover 🗺(U-NET FastAI library)

line_search_methods

The Algorithmic Showdown: Gradient Descent vs Newton's Method

module-scraping

predicting-poverty

Combining satellite imagery and machine learning to predict poverty

rl_automated_trading

In this project, we apply a deep Q-learning approach to algorithmic trading where our algorithmic trader determines when to buy, sell or hold based on the current and historical market data. 🤖📈

satisfaction_xgboost

In this project we build a xgboost model to classify individuals life satisfaction using the variables in the National Income Dynamic Studies (NIDS) database.

spatial_plots

Spatial plotting in R: an example using IEC voting data in South Africa.

super_resolution

Sattelite Image Super-Resolution using Convolution Neural Networks and Auto-encoders 🔭

text-mining

Class Folder for Text Mining for the Social Sciences @BGSE

text_mining_jobs

A basic introduction to text mining in R using the tidytext package on career24 job descriptions