Image by Author | Midjourney & Canva Introduction Choosing the right machine learning model for your data is of major importance in any data science project. The model you select will have a significant impact on the insights you derive from your data, and ultimately determine the usefulness of a project. In this article, we aim to provide practical tips to help new practitioners make informed decisions when choosing machine learning models. 1. Understand Your Data Understanding the type and […]

Image by Author Introduction Here’s a something that new machine learning practitioners figure out almost immediately: not all datasets are created equal. It may now seem obvious to you, but had you considered this before undertaking machine learning projects on a real world dataset? As an example of a single class vastly outnumbering the rest, take for instance some rare disease, which only 1% of the population has. Would a predictive model that only ever predicts “no disease” still be […]

Image by Author As a data professional, you should also know how to build predictive models with machine learning to solve business problems. And if you’re interested in machine learning, you’re probably also looking for the best resources to get going. Well, you can always choose a self-paced online course that best aligns with your learning preferences. But if you prefer learning from some of the best educators and experienced professionals—all for free—then YouTube is a great learning resource. This […]

Image by Author If you are a machine learning student, researcher, or practitioner, it is crucial for your career growth to have a deep understanding of how each algorithm works and the various techniques to enhance model performance. Nowadays, many individuals tend to focus solely on the code, data, and pre-trained models, often without fully comprehending the machine learning model’s algorithm or architecture. They simply fine-tune the model on a new dataset and adjust hyperparameters to improve performance. However, to […]