Regression is a robust statistical measurement for investigating the relationship between one or more independent (input features) variables and one dependent variable (output). In AI, regression is a supervised machine learning algorithm that can predict continuous numeric values. In simpler words, input features from the dataset are fed into the Read more…
Matthew’s correlation coefficient: A metric for imbalanced class problems Sometimes in data science and machine learning we encounter problems of imbalanced classes. These are problems when one class might have more instances than another. This makes accuracy a bad metric. If class A shows up 90% in our sample, and Read more…
By Yasmin Chamchoun Best languages for machine learning and data analytics Machine Learning Language can be defined as an application of machine learning for developing predictive models and algorithms that automate reasoning tasks with language data. Machine learning languages are difficult to learn and at times, frustrating. But they are revolutionizing Read more…
In a world that is driven by data and digital transformation it is absolutely vital that businesses have the right infrastructure, data strategy and solution set up early-on. This is where data architecture comes into play. What is Data Architecture? Data Architecture is a significant component required to gather and Read more…
By Yasmin Chamchoun The World Robotics Report released by The International Federation of Robotics in October 2018 revealed that the worldwide sales of robots in the workplace has rocketed in recent years. In 2017, there was $6.6 billion in sales volume in the service robot sector, a sharp increase of Read more…
Gradient boosted trees Gradient boosted trees is one of the most popular techniques in machine learning and for a good reason. It is one of the most powerful algorithms in existence, works fast and can give very good solutions. This is one of the reasons why there are many libraries Read more…
Cohen’s Kappa statistic is a very useful, but under-utilised, metric. Sometimes in machine learning we are faced with a multi-class classification problem. In those cases, measures such as the accuracy, or precision/recall do not provide the complete picture of the performance of our classifier. In some other cases we might Read more…
AI and machine learning are an excellent way to help SMEs achieve their goal of consistent business growth in today’s competitive environment. They allow SMEs to effectively delegate routine tasks to be done by innovative yet fast methods/technologies making executives free to focus on other creative avenues that can help Read more…
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…
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