Photo by Joris Berthelot on Unsplash

For the last couple of months I have been playing around with Streamlit as it is an awesome way of producing data science web applications with just one Python script.

The beauty of the technology is that it removes the requirements of having to programme the front end technology leaving you to focus on the good stuff — telling an engaging data story.

I work with a lot of survey information and I thought it would be interesting to build an application with the data we collected from a ski based survey.

There were a couple of reasons for my…


Building a webform to connect SQL and Python

Photo by Tobias Fischer on Unsplash

Recently I spent some time leveling-up my SQL skills so that I could write more complex queries and work with larger databases.

Once I had done this I wanted to apply my data structure knowledge to a project — I have experience with Django, having built a portfolio website with the framework, and as it ships with SQLite as default it is ready to go straight out of the box.

The idea of the project was to build a start-up landing page, where you could enter your details to join the newsletter…


Analysing global news headlines with NLTK’s Vader library.

Photo by NASA on Unsplash

Sentiment analysis is a branch of Natural Language Processing that allows data scientists to extract human emotion from a corpus of text.

It is a very important field of Machine Learning as it provides value and insight into the information that people have published, providing a better understanding of the digital ecosystem.

In this project I have used sentiment analysis to provide a real-time snapshot of the state of the world news based on three online news publications.

This has been achieved by extracting the headlines from The Guardian world news page…


Photo by Linus Nylund on Unsplash

The Brazilian Storm has seen surfers from the largest Latin American country dominate competitive surfing over recent years; but could this be the beginning of the end.

This machine learning project explores the makeup of the World Surf League (WSL) by nationality, how this has changed over time and what it will look like in the future.

The data has been extracted from the WSL website, by using Beautiful Soup to scrape the results tables. I wrote a script that pulls the key information from the tables starting at 2010 through to 2020 (a small dataset, we will revisit this)…


Search Volume Trend and Seasonality Analysis with Facebook Prophet

Photo by Benjamin Voros on Unsplash

The North Face has been one of the biggest brands on the global stage for both the fashion and the outdoor industry for the last few years. There has been a huge increase in the brand’s popularity, from starting as a small brand aimed at core enthusiasts in 1968 through to collaborating with some of the biggest hype brands today, such as Supreme.

This machine learning and predictive modelling project analyses The North Face’s worldwide Google search traffic to get an insight on whether the brand’s recent success will continue and how recent global events have impacted its digital footprint.

Giles Dean

Machine Learning and Artificial Neural Networks

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