Designing Machine Learning Systems with Python: Design efficient machine learning systems that give you more accurate results
โ Scribed by David Julian
- Publisher
- Packt Publishing
- Year
- 2016
- Tongue
- English
- Leaves
- 232
- Category
- Library
No coin nor oath required. For personal study only.
โฆ Synopsis
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.
๐ SIMILAR VOLUMES
<p><b>Design efficient machine learning systems that give you more accurate results</b></p><h2>About This Book</h2><ul><li>Gain an understanding of the machine learning design process</li><li>Optimize machine learning systems for improved accuracy</li><li>Understand common programming tools and tech
<p><b>Design efficient machine learning systems that give you more accurate results</b></p><h2>About This Book</h2><ul><li>Gain an understanding of the machine learning design process</li><li>Optimize machine learning systems for improved accuracy</li><li>Understand common programming tools and tech
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 ma
<div><p><strong>Summary</strong></p><p><em>Machine Learning Systems: Designs that scale</em> is an example-rich guide that teaches you how to implement reactive design solutions in your machine learning systems to make them as reliable as a well-built web app. </p><p>Foreword by Sean Owen, Director
<span>This book provides:</span><ul><li><span><span>End to end design of the most popular Machine Learning system at big tech companies.</span></span></li><li><span><span>Most common Machine Learning Design interview questions at big tech companies (Facebook, Apple, Amazon, Google, Uber, LinkedIn)</