Despite the seeming ubiquity of Machine Learning, only 39% of firms embed ML in daily business functions. This white paper demystifies Machine Learning for non-technical business stakeholders to better collaborate in, and derive more value from, data science initiatives. This paper covers:
- How ML differs from traditional computational problem solving
- Features and Labels and other data science jargon
- Types of machine learning - supervised, unsupervised, and reinforcement learning