Machine learning is one of the fastest growing trends in modern computing. It has applications in a wide range of fields, including economics, the natural sciences, web development, and business modeling. In order to harness the power of these systems, it is essential that the practitioner develops a solid understanding of the underlying design principles.
There are many reasons why machine learning models may not give accurate results. By looking at these systems from a design perspective, we gain a deeper understanding of the underlying algorithms and the optimisational methods that are available. This book will give you a solid foundation in the machine learning design process, and enable you to build customised machine learning models to solve unique problems. You may already know about, or have worked with, some of the
off-the-shelf machine learning models for solving common problems such as spam detection or movie classification, but to begin solving more complex problems, it is important to adapt these models to your own specific needs. This book will give you this understanding and more.

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Spis treści

Designing Machine Learning Systems with Python. Key design strategies to create intelligent systems eBook -- spis treści

• 1. Thinking in Machine Learning
• 2. Tools Overview
• 3. Turning data into information
• 4. Models: Learning from information
• 5. Linear Models
• 6. Neural nets
• 7. Features: How algorithms see the world
• 8. Learning with ensembles
• 9. Some real world examples