Blog

In this post, we will take a look at our approach to solve the problem of detecting snow and cloud patches in real world satellite images during the Copericus Hackathon 2020.

A look at various NLP tasks one can perform on text reviews to extract different kinds of information using machine learning

Göteborgsvarvet Part 3 - How to use machine learning to predict runner finishing times. We use a number of carefully engineered features to train multiple Ridge Regression models for half marathon finish time predictions at different stages of the race.

A dive into the world of finance and specifically financial options. We will have a look at how these contracts can be priced using Monte Carlo simulations.

An introduction to Monte Carlo simulations - an important concept in mathematical statistics. To exemplify these concepts we will look at option pricing, so we will take a small dive into the financial world as well.

Göteborgsvarvet Part 2 - We use checkpoint data to learn about pace and hubris, and how we can use this to our advantage in feature engineering

Göteborgsvarvet Part 1 - Introduction & general analysis of runners' finish times

Adventure planning and decision-making using KMeans clustering. A post about solving a real everyday life problem by grouping people with similar wishes using data analysis and machine learning.

A closer look at lightgbm, the mathematics behind gradient boosting and survival prediction for titanic passengers.

In this post, we will be focusing on text mining and review analysis. We’ll roll our own neural network implementation for relation extraction.