Supervised Machine Learning — SVM, Random Forest, Logistic Regression

This article assumes a basic understanding of machine learning algorithms and data science techniques.

Article outline:

  • Supervised machine learning
  • Classification — multi-class
  • Dataset — preliminary analysis & feature selection
  • Algorithm selection — SVM, Logistic Regression, Random Forest
  • Model performance — accuracy scores
  • Improvements — hyperparameter tuning & ensemble learning
  • Conclusions — more data!
Photo by Alexander Shatov on Unsplash

What is Supervised Machine Learning?

As with all technologies there are buzzwords, supervised learning is an umbrella term to describe an area of machine learning (the most frequently used in practice) where the data being used is labelled. The goal of a supervised learning algorithm is to leverage a dataset to produce…

Is there a correlation between FTSE100 closing prices?

Photo by Jamie Street on Unsplash

Supervised learning uses a trained algorithm to find patterns in a dataset. This article will focus on regression analysis, and how to build a suitable regression model to explain the variability in stock price of BAE systems using stock price data from other companies.

THE DATA — FTSE 100 Companies

The Financial Times Stock Exchange 100, also referred to as the FTSE 100, is an index composed of the 100 largest companies listed on the London Stock Exchange (LSE). The size of the company is determined by its Market Capitalization, which refers to the “total dollar market value of a company’s outstanding shares of stock” (Chen

K-means Cluster Analysis

This article is a continuation of my previous investigation into the trends of New York City’s condominium market.

Unsupervised Learning — Cluster Analysis

Photo by Hudson Hintze on Unsplash

Unsupervised learning encompasses a variety of machine learning techniques where the aim is to uncover hidden patterns within the data. This article will focus on cluster analysis, specifically K-means, a method of separating data into groups of similar objects.

K-means Clustering

K-Means is one of the most famous partitioning clustering algorithms and regarded as one of the most approachable forms of clustering. The goal of the algorithm is to find groups within the dataset, with the number of groups defined by ‘K. The algorithm…

Learn about the trends of New York City’s property market

New York City is one of the most densely populated cities on the planet, with nearly 8.4 million people living within 302 square miles.

Photo by Luca Bravo on Unsplash

Alongside accommodating an incredibly large and diversified population NYC possesses a property market of varied architectural styles. The market itself is regarded as one of the most expensive and competitive in the world. What is interesting when examining the American housing market as a whole, is the enormous price disparity between NYC and wider America. The growing gap in property prices is incredibly concerning. A modernized 350 square foot apartment in Manhattan’s SoHo neighbourhood has been…

Caelan Dwyer

MSc Data Analytics Student, with a background in economics and finance.

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