The document promotes the book 'Tuning Up: From A/B Testing to Bayesian Optimization' by David Sweet, which provides practical methods for optimizing engineered systems and enhancing project performance. It covers various experimental techniques applicable in competitive industries, includes practical code examples, and aims to deliver measurable improvements in user satisfaction and revenue. A discount code for 40% off the book is also offered.

1. Keep your systems
in top condition
with Tuning Up: From A/B testing to
Bayesian optimization.
Take 40% off by entering slsweet into
the discount code box at checkout at
manning.com.

2. Tuning an engineered system is best
done by following established
methods employed by high-
performing teams like the ones led
by author David Sweet.
This book reveals tests, metrics, and
practical tools that will ensure your
projects are constantly improving,
delivering revenue, and ensuring
user satisfaction.

3. Tuning Up: From A/B testing to Bayesian optimization is a toolbox of
experimental methods that will keep your software and systems working
at peak performance. You’ll learn to implement tests and techniques that
will boost the effectiveness of machine learning systems, trading
strategies, infrastructure, and more. Each method in this practical guide is
regularly utilized in highly competitive industries like finance and social
media.

4. This book teaches you proven methods for improving your production
systems. Each method has been tested in industry and is fully explained
using basic math and code written in Python and NumPy. By the time
you’re done, you’ll be able to seamlessly run effective performance
experiments while avoiding common mistakes and pitfalls.

5. What people are saying
about the book:
This book is the sure way ticket
to help you learn in an
interesting way using practical
code, probability, and real
world examples to design and
test your experiments.
-Satej Kumar Sahu
This book is a good
introduction to testing
and optimizations for
engineering systems
and applications.
-Anonymous reviewer

6. About the author:
David Sweet has worked as a
quantitative trader at GETCO and a
machine learning engineer at
Instagram, where he used
experimental methods to tune
trading systems and recommender
systems. This book is an extension
of his lectures on tuning
quantitative trading systems given
at NYU Stern over the past three
years.

7. Take 40% off Tuning Up: From A/B testing
to Bayesian optimization by entering
slsweet into the discount code box at
checkout at manning.com.
If you want to learn more about the
book, you can preview its contents on
our browser-based liveBook reader
here.