ML & Predictive Analytics

In today’s digital age, where online transactions and financial systems dominate, fraud has become a pervasive challenge for businesses. While digitization offers immense opportunities, it also exposes organizations to increasingly sophisticated schemes that pose significant risks, including financial losses, diminished customer trust, and reputational damage. A PwC report revealed that nearly half of organizations globally…

Sustainability has become one of the most pressing challenges of our time. From rising global temperatures to the depletion of natural resources, the need for action has never been more urgent. BBC mentions that human activities are responsible for approximately 1.5°C of global warming.  Artificial Intelligence can become our powerful ally in the fight for…

Machine learning uses programmatic algorithms to process user queries and generate an output. This output can be predicted labels (spam, not spam), clusters (customer segmentation), or a sequence of actions.   However, different machine learning algorithms help achieve various types of outputs. For example, supervised models generate predictions, and reinforcement models create a sequence of actions.  …

Mastering the ML project lifecycle is essential for leveraging the full potential of machine learning and bringing innovation through it. Careful implementation of each step guides towards impactful results.  Let’s explore the importance of the  ML lifecycle and how each step contributes to the project’s success. The Importance of Understanding the Machine Learning Lifecycle The…

All modern predictive models involving machine learning rely on statistical algorithms. Statistical techniques capture patterns within data which form the basis of data modeling and predictive analysis. Some of the basic patterns include mean, variance, and standard deviations. These statistical measures capture data distribution and allow machine-learning models to forecast unseen values. Let’s explore why…

AI, machine learning, data science, deep learning, we tend to use them interchangeably. While there are overlaps between these fields, they do have their own distinct characteristics and applications. In this post, we clarify these concepts providing a clear understanding of their roles, interconnections, and the distinct skill sets and tools required. Let’s dive in!…

Is there anything more frustrating than the potential of losing a customer? Perhaps they want to cancel their account because they aren’t using the tool enough to justify the costs. Maybe the key user has left the company and no one else has been trained to use it. Or it may be that the pricing…

As your marketing agency battles to win (and keep) clients in today’s competitive environment, finding a way to maintain an edge over your competition is a constant fight. One way to sharpen your agency’s value proposition is by leveling-up in an area that most agencies choose to put little effort into: client reporting. However, creating…