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.
