The Data Path Less Traveled - Zacharias Voulgaris - Bog

Become proficient in using heuristics within the data science pipeline to produce higher quality results in less time.

Although data professionals have used heuristics for many years within optimization-related applications, heuristics have been a vibrant area of research in various data-related areas, from machine learning to image processing. Heuristics also play a role in niche applications such as cybersecurity. In addition, the advent of AI and other data-driven methodologies have brought heuristics to the forefront of data-related work.

In this book, we explore heuristics from a practical perspective. We illustrate how heuristics can help you solve challenging problems through simple examples and real-life situations. Apply Jaccard Similarity and a variant, F1 score, Entropy, Ectropy, Area Under Curve, Particle Swarm Optimization, and Genetic Algorithms (along with GA variants). Beyond just exhibiting the various known and lesser-known heuristics available today, we also examine how you can go about creating your own through a simple and functional framework. Code notebooks enable you to practice all of the techniques and explore a few of your own.

There is no doubt that the data-driven paradigm is here to stay. There are many ways to stand out in it as a data professional, with AI-related know-how being at the top of the list. However, equally impactful can be the creative tools (heuristics) that make such technologies feasible and scalable. Unfortunately, this is a way that not many people care to follow as it's off the beaten path. Are you up for the challenge?