|
Showing 1 - 2 of
2 matches in All Departments
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.
This book is about the harmonious synthesis of functional
programming and numerical computation. It shows how the
expressiveness of OCaml allows for fast and safe development of
data science applications. Step by step, the authors build up to
use cases drawn from many areas of Data Science, Machine Learning,
and AI, and then delve into how to deploy at scale, using parallel,
distributed, and accelerated frameworks to gain all the advantages
of cloud computing environments. To this end, the book is divided
into three parts, each focusing on a different area. Part I begins
by introducing how basic numerical techniques are performed in
OCaml, including classical mathematical topics (interpolation and
quadrature), statistics, and linear algebra. It moves on from using
only scalar values to multi-dimensional arrays, introducing the
tensor and Ndarray, core data types in any numerical computing
system. It concludes with two more classical numerical computing
topics, the solution of Ordinary Differential Equations (ODEs) and
Signal Processing, as well as introducing the visualization module
we use throughout this book. Part II is dedicated to advanced
optimization techniques that are core to most current popular data
science fields. We do not focus only on applications but also on
the basic building blocks, starting with Algorithmic
Differentiation, the most crucial building block that in turn
enables Deep Neural Networks. We follow this with chapters on
Optimization and Regression, also used in building Deep Neural
Networks. We then introduce Deep Neural Networks as well as topic
modelling in Natural Language Processing (NLP), two advanced and
currently very active fields in both industry and academia. Part
III collects a range of case studies demonstrating how you can
build a complete numerical application quickly from scratch using
Owl. The cases presented include computer vision and recommender
systems. This book aims at anyone with a basic knowledge of
functional programming and a desire to explore the world of
scientific computing, whether to generally explore the field in the
round, to build applications for particular topics, or to deep-dive
into how numerical systems are constructed. It does not assume
strict ordering in reading - readers can simply jump to the topic
that interests them most.
|
You may like...
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
Sound Of Freedom
Jim Caviezel, Mira Sorvino, …
DVD
R325
R218
Discovery Miles 2 180
Loot
Nadine Gordimer
Paperback
(2)
R398
R330
Discovery Miles 3 300
|