This unique open access book applies the functional OCaml programming
language to numerical or computational weighted data science,
engineering, and scientific applications. This book is based on the
authors' first-hand experience building and maintaining Owl, an
OCaml-based numerical computing library.
You'll first learn the various components in a modern numerical
computation library. Then, you will learn how these components are
designed and built up and how to optimize their performance. After
reading and using this book, you'll have the knowledge required to
design and build real-world complex systems that effectively leverage
the advantages of the OCaml functional programming language.
What You Will Learn
- Optimize core operations based on N-dimensional arrays
- Design and implement an industry-level algorithmic differentiation
module
- Implement mathematical optimization, regression, and deep neural
network functionalities based on algorithmic differentiation
- Design and optimize a computation graph module, and understand the
benefits it brings to the numerical computing library
- Accommodate the growing number of hardware accelerators (e.g. GPU,
TPU) and execution backends (e.g. web browser, unikernel) of numerical
computation
- Use the Zoo system for efficient scripting, code sharing, service
deployment, and composition
- Design and implement a distributed computing engine to work with a
numerical computing library, providing convenient APIs and high
performance
Who This Book Is For
Those with prior programming experience, especially with the OCaml
programming language, or with scientific computing experience who may be
new to OCaml. Most importantly, it is for those who are eager to
understand not only how to use something, but also how it is built up.
