Metrics in machine learning As some of you might know, metrics in machine learning is one of my favourite topics. I have already spoken about RMSE and MAE, Cohen’s Kappa, the concordance correlation coefficient and other metrics. On this post, I’d like to talk about another very important metric: The Read more…
Note: This is an excerpt from my new book-in-progress called “Uncertainty”. The most popular definition of probability, and maybe the most intuitive, is the frequentist one. According to frequentists, an event’s probability is defined as the limit of this event’s frequency in a large number of trials. What does this Read more…
AI and creativity As many of you know, I am a big fan of the space of AI and creativity. This is a space I have worked on and blogged about in the past, and I am still active in. I am also the admin of the AI and Creativity Read more…
Data science is ever evolving, and with so many things going on it can be difficult to keep track of all the new libraries and algorithms. This is when it can be really useful to have a reference guide to help you out. Continuing from our series about cheatsheets, in Read more…
How much do you really know about the journey that a typical customer of your business takes to get to the stage of making a purchase? What are the main paths that customers follow, and what influences those paths? In an increasingly digitalised world, understanding the customer journey is becoming Read more…
Maintenance is a fact of business for companies in many industries. Therefore, making the process more efficient is a key priority and has been for many years. This applies to many industries, but the ones that benefit the most are the following: Manufacturing Freight Oil and gas Rail Shipping All Read more…
An Introduction to Anomaly Detection and Its Importance in Machine Learning Data is becoming increasingly important in almost every conceivable field and area. From business and healthcare to law enforcement and sports, data is central to their operations. It’s not enough to simply collect information however. Instead, you need to Read more…
In our first post about performance measures we talked about Cohen’s kappa. This time I want to talk about two different measures: The Root Mean Squared Error (RMSE) and the Mean Absolute Error (MAE). The RMSE is defined as: It is one of the most common metrics in regression, both in Read more…
Finance is one of the industries with the best adoption rates of machine learning and AI methods. This makes perfect sense since companies in finance all share, more or less, these features: They handle large volumes of data. They have a large number of employees accustomed to quantitative methods. Even Read more…
Today’s post is provided by Kite Table of Contents Introduction: balanced and imbalanced datasets What is data oversampling? What is SMOTE? How does SMOTE work? SMOTE tutorial using imbalanced-learn Base model Imbalanced model SMOTE’d model Recap and conclusion Introduction: balanced and imbalanced datasets Close your eyes. Now imagine a perfect Read more…
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