What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Description

Machine learning is the process of teaching machines to remember data patterns, using them to predict future outcomes, and offering choices that would appeal to individuals based on their past preferences. Machine learning is applicable to a lot of what you do every day. As a result, you can’t take forever to deliver your first iteration of software. Learning to build machine learning algorithms within a controlled test framework will speed up your time to deliver, quantify quality expectations with your clients, and enable rapid iteration and collaboration. This book will show you how to quantifiably test machine learning algorithms. The very different, foundational approach of this book starts every example algorithm with the simplest thing that could possibly work. With this approach, seasoned veterans will find simpler approaches to beginning a machine learning algorithm. You will learn how to iterate on these algorithms to enable rapid delivery and improve performance expectations. The book begins with an introduction to test driving machine learning and quantifying model quality. From there, you will test a neural network, predict values with regression, and build upon regression techniques with logistic regression. You will discover how to test different approaches to naïve bayes and compare them quantitatively, along with how to apply OOP (Object-Oriented Programming) and OOP patterns to test-driven code, leveraging SciKit-Learn. Finally, you will walk through the development of an algorithm which maximizes the expected value of profit for a marketing campaign by combining one of the classifiers covered with the multiple regression example in the book.

What you will learn

Get started with an introduction to testdriven development and familiarize yourself with how to apply these concepts to machine learning

Build and test a neural network deterministically, and learn to look for niche cases that cause odd model behaviour

Learn to use the multiarmed bandit algorithm to make optimal choices in the face of an enormous amount of uncertainty

Generate complex and simple random data to create a wide variety of test cases that can be codified into tests

Develop models iteratively, even when using a thirdparty library

Quantify model quality to enable collaboration and rapid iteration

Adopt simpler approaches to common machine learning algorithms

Use behaviourdriven development principles to articulate test intent

What do you get with Print?

Instant access to your digital copy whilst your Print order is Shipped

Paperback book shipped to your preferred address

Redeem a companion digital copy on all Print orders

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

Frequently bought together

$50.99

$48.99

$26.99

Total $ 126.97

FAQs

What is the digital copy I get with my Print order?

When you buy any Print edition of our Books, you can redeem (for free) the eBook edition of the Print Book you’ve purchased. This gives you instant access to your book when you make an order via PDF, EPUB or our online Reader experience.

What is the delivery time and cost of print book?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

Economy: Can deliver to P. O. Boxes and private residences.
Trackable service with delivery to addresses in Australia only.
Delivery time ranges from 7-9 business days for VIC and 8-10 business days for Interstate metro
Delivery time is up to 15 business days for remote areas of WA, NT & QLD.

Premium: Delivery to addresses in Australia only
Trackable delivery to most P. O. Boxes and private residences in Australia within 4-5 days based on the distance to a destination following dispatch.

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Disclaimer:
All orders received before 5 PM U.K time would start printing from the next business day. So the estimated delivery times start from the next day as well. Orders received after 5 PM U.K time (in our internal systems) on a business day or anytime on the weekend will begin printing the second to next business day. For example, an order placed at 11 AM today will begin printing tomorrow, whereas an order placed at 9 PM tonight will begin printing the day after tomorrow.

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

What is custom duty/charge?

Customs duty are charges levied on goods when they cross international borders. It is a tax that is imposed on imported goods. These duties are charged by special authorities and bodies created by local governments and are meant to protect local industries, economies, and businesses.

Do I have to pay customs charges for the print book order?

The orders shipped to the countries that are listed under EU27 will not bear custom charges. They are paid by Packt as part of the order.

List of EU27 countries: www.gov.uk/eu-eea:

A custom duty or localized taxes may be applicable on the shipment and would be charged by the recipient country outside of the EU27 which should be paid by the customer and these duties are not included in the shipping charges been charged on the order.

How do I know my custom duty charges?

The amount of duty payable varies greatly depending on the imported goods, the country of origin and several other factors like the total invoice amount or dimensions like weight, and other such criteria applicable in your country.

For example:

If you live in Mexico, and the declared value of your ordered items is over $ 50, for you to receive a package, you will have to pay additional import tax of 19% which will be $ 9.50 to the courier service.
Whereas if you live in Turkey, and the declared value of your ordered items is over € 22, for you to receive a package, you will have to pay additional import tax of 18% which will be € 3.96 to the courier service.

How can I cancel my order?

Cancellation Policy for Published Printed Books:

You can cancel any order within 1 hour of placing the order. Simply contact customercare@packt.com with your order details or payment transaction id. If your order has already started the shipment process, we will do our best to stop it. However, if it is already on the way to you then when you receive it, you can contact us at customercare@packt.com using the returns and refund process.

Please understand that Packt Publishing cannot provide refunds or cancel any order except for the cases described in our Return Policy (i.e. Packt Publishing agrees to replace your printed book because it arrives damaged or material defect in book), Packt Publishing will not accept returns.

What is your returns and refunds policy?

Return Policy:

We want you to be happy with your purchase from Packtpub.com. We will not hassle you with returning print books to us. If the print book you receive from us is incorrect, damaged, doesn't work or is unacceptably late, please contact Customer Relations Team on customercare@packt.com with the order number and issue details as explained below:

If you ordered (eBook, Video or Print Book) incorrectly or accidentally, please contact Customer Relations Team on customercare@packt.com within one hour of placing the order and we will replace/refund you the item cost.
Sadly, if your eBook or Video file is faulty or a fault occurs during the eBook or Video being made available to you, i.e. during download then you should contact Customer Relations Team within 14 days of purchase on customercare@packt.com who will be able to resolve this issue for you.
You will have a choice of replacement or refund of the problem items.(damaged, defective or incorrect)
Once Customer Care Team confirms that you will be refunded, you should receive the refund within 10 to 12 working days.
If you are only requesting a refund of one book from a multiple order, then we will refund you the appropriate single item.
Where the items were shipped under a free shipping offer, there will be no shipping costs to refund.

On the off chance your printed book arrives damaged, with book material defect, contact our Customer Relation Team on customercare@packt.com within 14 days of receipt of the book with appropriate evidence of damage and we will work with you to secure a replacement copy, if necessary. Please note that each printed book you order from us is individually made by Packt's professional book-printing partner which is on a print-on-demand basis.

What tax is charged?

Currently, no tax is charged on the purchase of any print book (subject to change based on the laws and regulations). A localized VAT fee is charged only to our European and UK customers on eBooks, Video and subscriptions that they buy. GST is charged to Indian customers for eBooks and video purchases.

What payment methods can I use?

You can pay with the following card types:

Visa Debit
Visa Credit
MasterCard
PayPal

What is the delivery time and cost of print books?

Shipping Details

USA:

Economy: Delivery to most addresses in the US within 10-15 business days

Premium: Trackable Delivery to most addresses in the US within 3-8 business days

UK:

Economy: Delivery to most addresses in the U.K. within 7-9 business days.
Shipments are not trackable

Premium: Trackable delivery to most addresses in the U.K. within 3-4 business days!
Add one extra business day for deliveries to Northern Ireland and Scottish Highlands and islands

EU:

Premium: Trackable delivery to most EU destinations within 4-9 business days.

Australia:

India:

Premium: Delivery to most Indian addresses within 5-6 business days

Rest of the World:

Premium: Countries in the American continent: Trackable delivery to most countries within 4-7 business days

Asia:

Premium: Delivery to most Asian addresses within 5-9 business days

Unfortunately, due to several restrictions, we are unable to ship to the following countries:

Afghanistan
American Samoa
Belarus
Brunei Darussalam
Central African Republic
The Democratic Republic of Congo
Eritrea
Guinea-bissau
Iran
Lebanon
Libiya Arab Jamahriya
Somalia
Sudan
Russian Federation
Syrian Arab Republic
Ukraine
Venezuela

Julian Cook Jan 27, 2016

This is a totally out-of-left-field book on machine learning. Not only is it novel, but I think the ideas will become more important over time, as more models move into production scenarios and need to be iteratively changed and improved, whilst not _breaking_ the model that already works.The main idea, as you may have guessed, is to change the model development process from exploring data - followed by trying different models, to a more formal approach of wrapping your data in a test framework and then proceeding to develop the model(s).The initial model (or failing test) can just be a random guesser, after this you continually re-factor your code to improve on the random result or previous iteration of the model (at which point the test passes).This will seem weird to a statistician, who would insist of emphasizing significance tests or (at least) looking at an ROC curve, which this book also does. The point made by the author is that once you enter the real world of running prediction models in production, you need to move to a process of iterative development, where you have some formal guarantee that the new model is better than the last and that you have not somehow fooled yourself into using something that is not much better than random.There are a couple of drawbacks to the whole approach though. The first is the pain of setting up the tests in the first place, especially when you have a lot of data. I thought about setting up some synthetic data to test a new model, but it was honestly quicker to step through an example with the real data to figure out whether the code was working or not.The other issue is with interactive environments, like R and ipython, you can write your code in short sections at the console, then test each section, or model iteration, as you go. This is very efficient and doesn't necessarily work with a 'think up the tests before you do anything' approach.Even if you don't like the ideas, the book itself is still a very good way to approach statistical model development and should be widely read, especially in organizations where multiple people might touch the ML code.

Amazon Verified review

Bill Jan 17, 2017

I have no disagreements whatsoever with the main point of this book--creating a comprehensive suite of tests is a critical step of building quality ML tools. However, when describing this process for various ML models, the tests described by the author are incredibly trivial. If you know nothing about building ML models, then this book could be valuable for you. If you are even a moderately experienced practitioner, this book is a waste of your time. In my opinion, the entire text could be boiled down to the following 3 sentences1. You should have tests for your ML tools2. You should have tests to make sure your tools perform as you expect they would, at a very basic level (as you should do with any code you write)3. You should have tests to make sure your tools meet appropriate performance benchmarks on a handful of appropriate toy problemsNothing proposed by the author is a bad idea, it's just trivial. I learned nothing.

Martin Aug 03, 2020

This book attempts to introduce test-driven development to data scientists.Because of this I had hoped to find answers to questions specific to machinelearning which other books about test-driven development in general do notconsider. My questions (in particular, how to deal with statistical uncertaintyin tests and how to keep the test suite fast) were touched superficially at best.The book could have been a real gem, sitting at the sweet spot where the topicstest-driven development and machine learning intersect. Instead, it tries to bean introductory text in both fields and falls short. There are better introductorybooks specifically for either topic.The quality of the text and code examples is low. The text contains ambiguousformulations, discrepancies, and topics that are introduced but not furtherdiscussed. The code examples are carelessly formatted, contain obvious copy&pastemistakes, and syntax errors. The occasional mistake in a technical book is usuallyno big deal, but their sheer amount made reading this book an annoying experience.All that said, this book could be interesting for a reader who has had priorexposure to the topics being covered and is committed to work through them indetail to elaborate on what the examples show and what is left unsaid.

Test Driven Machine Learning: Control your machine learning algorithms using test-driven development to achieve quantifiable milestones

What do you get with Print?