Authors Alfred Essa and Shirin Mojarad provide a gentle introduction to foundational topics in AI. Each topic is framed as a triad: concept, theory, and practice. The concept chapters develop the intuition, culminating in a practical case study. The theory chapters reveal the underlying technical machinery. The practice chapters provide code in Python to implement the models discussed in the case study.
With this book, readers will learn:
- The technical foundations of machine learning and deep learning
- How to apply the core technical concepts to solve business problems
- The different methods used to evaluate AI models
- How to understand model development as a tradeoff between accuracy and generalization
- How to represent the computational aspects of AI using vectors and matrices
- How to express the models in Python by using machine learning libraries such as scikit-learn, statsmodels, and keras
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