What do you get with a Packt Subscription?

Free for first 7 days. $15.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

Key benefits

Learn how to extract easy-to-understand insights from any machine learning model

Become well-versed with interpretability techniques to build fairer, safer, and more reliable models

Mitigate risks in AI systems before they have broader implications by learning how to debug black-box models

Description

Do you want to gain a deeper understanding of your models and better mitigate poor prediction risks associated with machine learning interpretation? If so, then Interpretable Machine Learning with Python deserves a place on your bookshelf. We’ll be starting off with the fundamentals of interpretability, its relevance in business, and exploring its key aspects and challenges. As you progress through the chapters, you'll then focus on how white-box models work, compare them to black-box and glass-box models, and examine their trade-off. You’ll also get you up to speed with a vast array of interpretation methods, also known as Explainable AI (XAI) methods, and how to apply them to different use cases, be it for classification or regression, for tabular, time-series, image or text. In addition to the step-by-step code, this book will also help you interpret model outcomes using examples. You’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability. The methods you’ll explore here range from state-of-the-art feature selection and dataset debiasing methods to monotonic constraints and adversarial retraining. By the end of this book, you'll be able to understand ML models better and enhance them through interpretability tuning.

Who is this book for?

This book is primarily written for data scientists, machine learning developers, and data stewards who find themselves under increasing pressures to explain the workings of AI systems, their impacts on decision making, and how they identify and manage bias. It’s also a useful resource for self-taught ML enthusiasts and beginners who want to go deeper into the subject matter, though a solid grasp on the Python programming language and ML fundamentals is needed to follow along.

What you will learn

Recognize the importance of interpretability in business

Study models that are intrinsically interpretable such as linear models, decision trees, and Naïve Bayes

Become well-versed in interpreting models with model-agnostic methods

Visualize how an image classifier works and what it learns

Understand how to mitigate the influence of bias in datasets

Discover how to make models more reliable with adversarial robustness

Use monotonic constraints to make fairer and safer models

What do you get with a Packt Subscription?

Free for first 7 days. $15.99 p/m after that. Cancel any time!

Unlimited ad-free access to the largest independent learning library in tech. Access this title and thousands more!

50+ new titles added per month, including many first-to-market concepts and exclusive early access to books as they are being written.

Innovative learning tools, including AI book assistants, code context explainers, and text-to-speech.

Thousands of reference materials covering every tech concept you need to stay up to date.

Subscribe now

View plans & pricing

Frequently bought together

Interpretable Machine Learning with Python

$54.99

$52.99

Machine Learning for Algorithmic Trading

$57.99

Total $ 165.97

FAQs

What is included in a Packt subscription?

A subscription provides you with full access to view all Packt and licnesed content online, this includes exclusive access to Early Access titles. Depending on the tier chosen you can also earn credits and discounts to use for owning content

How can I cancel my subscription?

To cancel your subscription with us simply go to the account page - found in the top right of the page or at https://subscription.packtpub.com/my-account/subscription - From here you will see the ‘cancel subscription’ button in the grey box with your subscription information in.

What are credits?

Credits can be earned from reading 40 section of any title within the payment cycle - a month starting from the day of subscription payment. You also earn a Credit every month if you subscribe to our annual or 18 month plans. Credits can be used to buy books DRM free, the same way that you would pay for a book. Your credits can be found in the subscription homepage - subscription.packtpub.com - clicking on ‘the my’ library dropdown and selecting ‘credits’.

What happens if an Early Access Course is cancelled?

Projects are rarely cancelled, but sometimes it's unavoidable. If an Early Access course is cancelled or excessively delayed, you can exchange your purchase for another course. For further details, please contact us here.

Where can I send feedback about an Early Access title?

If you have any feedback about the product you're reading, or Early Access in general, then please fill out a contact form here and we'll make sure the feedback gets to the right team.

Can I download the code files for Early Access titles?

We try to ensure that all books in Early Access have code available to use, download, and fork on GitHub. This helps us be more agile in the development of the book, and helps keep the often changing code base of new versions and new technologies as up to date as possible. Unfortunately, however, there will be rare cases when it is not possible for us to have downloadable code samples available until publication.

When we publish the book, the code files will also be available to download from the Packt website.

How accurate is the publication date?

The publication date is as accurate as we can be at any point in the project. Unfortunately, delays can happen. Often those delays are out of our control, such as changes to the technology code base or delays in the tech release. We do our best to give you an accurate estimate of the publication date at any given time, and as more chapters are delivered, the more accurate the delivery date will become.

How will I know when new chapters are ready?

We'll let you know every time there has been an update to a course that you've bought in Early Access. You'll get an email to let you know there has been a new chapter, or a change to a previous chapter. The new chapters are automatically added to your account, so you can also check back there any time you're ready and download or read them online.

I am a Packt subscriber, do I get Early Access?

Yes, all Early Access content is fully available through your subscription. You will need to have a paid for or active trial subscription in order to access all titles.

How is Early Access delivered?

Early Access is currently only available as a PDF or through our online reader. As we make changes or add new chapters, the files in your Packt account will be updated so you can download them again or view them online immediately.

How do I buy Early Access content?

Early Access is a way of us getting our content to you quicker, but the method of buying the Early Access course is still the same. Just find the course you want to buy, go through the check-out steps, and you’ll get a confirmation email from us with information and a link to the relevant Early Access courses.

What is Early Access?

Keeping up to date with the latest technology is difficult; new versions, new frameworks, new techniques. This feature gives you a head-start to our content, as it's being created. With Early Access you'll receive each chapter as it's written, and get regular updates throughout the product's development, as well as the final course as soon as it's ready.We created Early Access as a means of giving you the information you need, as soon as it's available. As we go through the process of developing a course, 99% of it can be ready but we can't publish until that last 1% falls in to place. Early Access helps to unlock the potential of our content early, to help you start your learning when you need it most. You not only get access to every chapter as it's delivered, edited, and updated, but you'll also get the finalized, DRM-free product to download in any format you want when it's published. As a member of Packt, you'll also be eligible for our exclusive offers, including a free course every day, and discounts on new and popular titles.

Filter reviews by

All

Amazon verified reviews

Milin desai Apr 15, 2021

I've been reading this book from last over 2 weeks, and the way Author presented the concept are really interesting, and even if you don't have any technical background still you will be able to interpret and understand all the concepts. I should say I've learned more from this book than the 3 hours college classes at the university.if you are someone who is interested learning about machine learning focusing with python. This book is perfect you and for all levels, I was some where between the beginner and intermediate level but found this book really helpful.Thank you Serg for writing this wonder piece of tech art.

Amazon Verified review

N. J. Cruz Jun 19, 2021

I’m a computational neuroscientist in training, and in this field (and in related fields) we always try to find biologically plausible models. While this book does not delve into what mother nature does, it provides a beautiful catalog of methods and explanations for how to apply state of the art machine learning techniques and what they actually might mean when used. Importantly, it provides post-hoc methods to explain what many others have taken for granted with today’s easy to use, out of the box machine learning techniques. I’ll be using this as a reference for many of my future projects.

TF Jun 01, 2021

I received a free copy of this book in exchange for my honest review.Coming from an actuarial pricing background, the adoption of machine learning methods, however popular, has been limited for transparency and regulatory reasons. The need for interpretable models is paramount to reassure the regulators and the public that the ratemaking principles such as fairness, accountability and transparency in technical models are met. This is a recurrent theme in this book: how to make models “safe, fair and reliable”.I enjoyed reading this book for its simplicity and its ethical and practical approach. There are diverse use cases to go through with available Python codes. The mathematical properties behind these interpretable methods are not developed in this book. This is a hands-on approach that gives you the necessary tools WITH the insight on why and how to deploy these methods as a practitioner of machine learning models.

conanlover6 Aug 16, 2021

This book goes into great depth and helps a lot to understand what interpretability is. Recommended for those new to the field as well as veterans.

Aren Carpenter Oct 02, 2021

This book is the perfect next step for data science intermediates or motivated beginners to get hands on experience with real-world scenarios. It is approachable and Serg explains complicated topics deftly. I highly recommend making it your next ML book.

Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples

What do you get with a Packt Subscription?

Key benefits

Description

Who is this book for?

What you will learn

Product Details

What do you get with a Packt Subscription?

Product Details

Frequently bought together

Recommendations for you

Customer reviews

Filter reviews by

People who bought this also bought

About the author

FAQs

Interpretable Machine Learning with Python: Learn to build interpretable high-performance models with hands-on real-world examples

What do you get with a Packt Subscription?

Key benefits

Description

Who is this book for?

What you will learn

Product Details

What do you get with a Packt Subscription?

Product Details

Packt Subscriptions

Frequently bought together

Recommendations for you

Customer reviews

Filter reviews by

People who bought this also bought

About the author

FAQs