Do you agree we are approaching the tipping point in the history of our planet? Sounds dramatic, doesn’t it? And unfortunately, it is as serious as it sounds. Over the years there have been many warnings about the imminent dangers looming over our cherished planet but not many tangible actions…

Boosting performance is a priority in the AI space. Businesses will not hesitate to make large investments to achieve even a marginal improvement (e.g. increased accuracy, speed) in AI systems. …

Data science is a field that encapsulates a range of skills. However, in the data scientist’s toolbox, coding might become an underrated tool. In order to derive optimal results, a data scientist may choose to focus on a mathematical or conceptual component of their data science task. This strategy might…

The applications of AI in the financial sector are multi-faceted. In this article, we explore some key use cases of AI for hedge funds. We also look at potential challenges in implementing AI-based solutions, and how hedge funds can circumvent these challenges. In an analysis done in 2020, consulting and…

AI is a sector that is often perceived as having both positive and negative impacts on the environment. On the one hand, AI is able to provide innovative and scalable solutions to tackle the root causes of climate change . Measuring and reducing emissions at scale and enabling innovative business…

In our previous article, Customer Churn Prediction and Prevention Using AI , we pointed out the role of AI in predicting and preventing customer churn. We mentioned that it can cost between 6 to 7 times more to get a new customer, when compared with retaining an existing customer. …

Forecasting is a crucial component in decision-making. In order to make good decisions in the present, we must be able to, at least with some accuracy, anticipate future events and the consequences of our actions on those future incidents. Time Series Forecasting Machine learning can be applied to time series data in order…

There are several concerns when selecting machine learning models for a specific task. The model performance is of course a prime concern. Besides, the model complexity and speed are vital in scenarios requiring a fast deployment or quick response from models. …

Hyperparameter tuning plays an important role in the process of training an optimal machine learning model. …