Fundamentals of optimization theory with applications to machine learning
โ Scribed by Gallier J., Quaintance J
- Year
- 2019
- Tongue
- English
- Leaves
- 832
- Edition
- draft
- Category
- Library
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
Volume 2 applies the linear algebra concepts presented in Volume 1 to optimization problems which frequently occur throughout Machine Learning. This book blends theory with practice by not only carefully discussing the mathematical under pinnings of each optimization technique but by applying these
<p><span>The book reviews core concepts of machine learning (ML) while focusing on modern applications. It is aimed at those who want to advance their understanding of ML by providing technical and practical insights. It does not use complicated mathematics to explain how to benefit from ML algorith
The primary goal of this text is a practical one. Equipping students with enough knowledge and creating an independent research platform, the author strives to prepare students for professional careers. Providing students with a marketable skill set requires topics from many areas of optimization. T