Andriy Burkov

Follow to get new release updates and improved recommendations

About Andriy Burkov

Andriy Burkov is a dad of two and a machine learning expert based in Quebec City, Canada. Eleven years ago, he got a Ph.D. in Artificial Intelligence, and for the last eight years, he's been leading a team of machine learning developers at Gartner.

His specialty is natural language processing. His team works on building state-of-the-art multilingual text extraction and normalization systems for production, using both shallow and deep learning technologies.

Are you an author?

Help us improve our Author Pages by updating your bibliography and submitting a new or current image and biography.

Learn more at Author Central

1 11 1

$37.95

Kindle Edition
$34.95

Kindle Edition
$38.99

Kindle Edition
$34.82

Kindle Edition
$30.95

Kindle Edition
$37.49

Kindle Edition
$25.99

Kindle Edition
$65.56

Tankobon Softcover

Author Updates

Titles By Andriy Burkov

All Formats Kindle Edition Hardcover Paperback

The Hundred-Page Machine Learning Book Jan 12, 2019

by Andriy Burkov

( 189 )

$37.95

WARNING: will not work on e-ink Kindle devices!

Peter Norvig, Research Director at Google, co-author of AIMA, the most popular AI textbook in the world: "Burkov has undertaken a very useful but impossibly hard task in reducing all of machine learning to 100 pages. He succeeds well in choosing the topics — both theory and practice — that will be useful to practitioners, and for the reader who understands that this is the first 100 (or actually 150) pages you will read, not the last, provides a solid introduction to the field."

Aurélien Géron, Senior AI Engineer, author of the bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "The breadth of topics the book covers is amazing for just 100 pages (plus few bonus pages!). Burkov doesn't hesitate to go into the math equations: that's one thing that short books usually drop. I really liked how the author explains the core concepts in just a few words. The book can be very useful for newcomers in the field, as well as for old-timers who can gain from such a broad view of the field."

Karolis Urbonas, Head of Data Science at Amazon: "A great introduction to machine learning from a world-class practitioner."

Chao Han, VP, Head of R&D at Lucidworks: "I wish such a book existed when I was a statistics graduate student trying to learn about machine learning."

Sujeet Varakhedi, Head of Engineering at eBay: "Andriy's book does a fantastic job of cutting the noise and hitting the tracks and full speed from the first page.''

Deepak Agarwal, VP of Artificial Intelligence at LinkedIn: "A wonderful book for engineers who want to incorporate ML in their day-to-day work without necessarily spending an enormous amount of time.''

Vincent Pollet, Head of Research at Nuance: "The Hundred-Page Machine Learning Book is an excellent read to get started with Machine Learning.''

Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: "This is a compact “how to do data science” manual and I predict it will become a go-to resource for academics and practitioners alike. At 100 pages (or a little more), the book is short enough to read in a single sitting. Yet, despite its length, it covers all the major machine learning approaches, ranging from classical linear and logistic regression, through to modern support vector machines, deep learning, boosting, and random forests. There is also no shortage of details on the various approaches and the interested reader can gain further information on any particular method via the innovative companion book wiki. The book does not assume any high level mathematical or statistical training or even programming experience, so should be accessible to almost anyone willing to invest the time to learn about these methods. It should certainly be required reading for anyone starting a PhD program in this area and will serve as a useful reference as they progress further. Finally, the book illustrates some of the algorithms using Python code, one of the most popular coding languages for machine learning.

Other Formats: Hardcover , Paperback

Machine Learning Engineering Sep 4, 2020

by Andriy Burkov

( 127 )

$34.95

WARNING: will not work on e-ink Kindle devices!
From the author of a world bestseller published in eleven languages, The Hundred-Page Machine Learning Book, this new book by Andriy Burkov is the most complete applied AI book out there. It is filled with best practices and design patterns of building reliable machine learning solutions that scale. Andriy Burkov has a Ph.D. in AI and is the leader of a machine learning team at Gartner. This book is based on Andriy's own 15 years of experience in solving problems with AI as well as on the published experience of the industry leaders.

Here's what Cassie Kozyrkov, Chief Decision Scientist at Google tells about the book in the Foreword:

"You're looking at one of the few true Applied Machine Learning books out there. That's right, you found one! A real applied needle in the haystack of research-oriented stuff. Excellent job, dear reader... unless what you were actually looking for is a book to help you learn the skills to design general-purpose algorithms, in which case I hope the author won't be too upset with me for telling you to flee now and go pick up pretty much any other machine learning book. This one is different."
[...]
"So, what's in [...] the book? The machine learning equivalent of a bumper guide to innovating in recipes to make food at scale. Since you haven't read the book yet, I'll put it in culinary terms: you'll need to figure out what's worth cooking / what the objectives are (decision-making and product management), understand the suppliers and the customers (domain expertise and business acumen), how to process ingredients at scale (data engineering and analysis), how to try many different ingredient-appliance combinations quickly to generate potential recipes (prototype phase ML engineering), how to check that the quality of the recipe is good enough to serve (statistics), how to turn a potential recipe into millions of dishes served efficiently (production phase ML engineering), and how to ensure that your dishes stay top-notch even if the delivery truck brings you a ton of potatoes instead of the rice you ordered (reliability engineering). This book is one of the few to offer perspectives on each step of the end-to-end process."
[...]
"One of my favorite things about this book is how fully it embraces the most important thing you need to know about machine learning: mistakes are possible... and sometimes they hurt. As my colleagues in site reliability engineering love to say, "Hope is not a strategy." Hoping that there will be no mistakes is the worst approach you can take. This book does so much better. It promptly shatters any false sense of security you were tempted to have about building an AI system that is more "intelligent" than you are. (Um, no. Just no.) Then it diligently takes you through a survey of all kinds of things that can go wrong in practice and how to prevent/detect/handle them. This book does a great job of outlining the importance of monitoring, how to approach model maintenance, what to do when things go wrong, how to think about fallback strategies for the kinds of mistakes you can't anticipate, how to deal with adversaries who try to exploit your system, and how to manage the expectations of your human users (there's also a section on what to do when your, er, users are machines). These are hugely important topics in practical machine learning, but they're so often neglected in other books. Not here.

Other Formats: Hardcover , Paperback

The Hundred-Page Machine Learning Book en español (Spanish Edition) Oct 6, 2019

by Andriy Burkov , Antoni Munar , Carl Handlin

( 7 )

$38.99

Peter Norvig, Director de Investigación en Google, coautor de AIMA, uno de los libros de texto en IA más utilizados en el mundo: "Burkov ha acometido la muy util pero casi imposible y durísima tarea de reducir todo el aprendizaje automático a 100 páginas. Su éxito total al escoger los temas -tanto teóricos como prácticos- será de gran utilidad para los profesionales, y para el lector que es consciente de que están son las primeras 100 (en realidad 150 páginas) que leerá del tema, pero que no serán las últimas, proporciona una sólida introducción a la materia."

Aurélien Géron, Ingeniero Senior en IA, autor del bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "La amplitud de los temas que el libro cubre en solo 100 páginas (¡algunas más como extra!) es asombrosa. Burkov no duda en entrar en las fórmulas matemáticas, algo que en los libros cortos se suele evitar. Realmente me ha gustado como el autor explica los conceptos fundamentales en solo unas pocas palabras. El libro puede ser muy útil tanto a los principiantes en el campo, como a los más experimentados, que sin duda hallarán valor en una visión tan amplia del campo."

Karolis Urbonas, Jefe de Ciencia de Datos en Amazon: "Una gran introducción al aprendizaje automático por parte de un profesional de clase mundial."

Chao Han, VP, Jefe de I&D en Lucidworks: "Ojalá hubiera tenido un libro así cuando era un estudiante de estadística tratando de aprender sobre aprendizaje automático."

Sujeet Varakhedi, Jefe de Ingeniería en eBay: "El libro de Andriy hace un trabajo fantástico explicando los conceptos de manera concisa y a toda velocidad desde la primera página.''

Deepak Agarwal, VP de Inteligencia Artificial en LinkedIn: "Un libro maravilloso para los ingenieros que deseen incorporar el aprendizaje automático en su trabajo diario sin tener que gastar una cantidad enorme de tiempo.''

Vincent Pollet, Jefe de Investigación en Nuance: "Excelente lectura para comenzar con el aprendizaje automático.''

Gareth James, Professor of Data Sciences and Operations, co-author of the bestseller An Introduction to Statistical Learning, with Applications in R: "Este es un manual compacto de "cómo hacer ciencia de datos" y predigo que se convertirá en un recurso para académicos y profesionales por igual. Con poco más de 100 páginas, el libro es lo suficientemente corto como para leerlo de una sola vez. Sin embargo, a pesar de su extensión, cubre todos los enfoques principales de aprendizaje automático, que van desde la regresión lineal y la regresión logística, hasta las modernas máquinas de vectores de soporte, aprendizaje profundo, gradient boosting y bosques aleatorios. Tampoco faltan detalles sobre los diversos enfoques y el lector interesado puede obtener más información sobre cualquier método en particular a través de la innovadora wiki complementaria.

Other Formats: Paperback

The Hundred-Page Machine Learning Book em português (Portuguese Edition) Oct 28, 2019

by Andriy Burkov , Rodrigo Amaro e Silva , Márcio Moraes de Andrade

$34.82

Peter Norvig, Diretor de Pesquisa do Google, coautor do AIMA, o livro de IA mais popular do mundo. "Burkov assumiu uma tarefa muito útil, mas incrivelmente difícil, de reduzir todo o aprendizado de máquina a 100 páginas. Ele conseguiu escolher bem os tópicos — tanto teóricos quanto práticos — que serão úteis para os profissionais e para o leitor que entender que estas são as 100 (ou, de fato, 150) primeiras, e não as últimas, páginas que ele lerá e que lhe fornecerão uma introdução sólida para a área."

Aurélien Géron, Engenheiro Sênior de IA, autor do bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "A variedade de tópicos que o livro cobre é incrível para apenas 100 páginas (mais algumas de bônus!). Burkov não hesita em entrar nas equações matemáticas: que é uma coisa que os livros curtos costumam deixar de fora. Eu realmente gostei de como o autor explica os conceitos principais em apenas algumas poucas palavras. O livro pode ser muito útil para iniciantes na área, bem como para veteranos que podem se beneficiar de uma visão tão ampla."

Karolis Urbonas, Chefe de Ciência de Dados da Amazon: "Uma ótima introdução à Aprendizagem de Máquina de um profissional de classe mundial."

Chao Han, VP, Chefe de Pesquisa e Desenvolvimento da Lucidworks: "Eu gostaria que um livro como esse existisse quando eu era um estudante de graduação em Estatística tentando aprender sobre Aprendizagem de Máquina."

Sujeet Varakhedi, Chefe de Engenharia da eBay: "O livro de Andriy faz um trabalho fantástico de cortar o ruído e atingir as faixas e a velocidade máxima desde a primeira página.''

Deepak Agarwal, VP de Inteligência Artificial do LinkedIn: "Um livro maravilhoso para engenheiros que desejam incorporar Aprendizagem de Máquina em seu trabalho diário sem necessariamente gastar uma quantidade enorme de tempo.''

Vincent Pollet, Chefe de Pesquisas da Nuance: "Excelente leitura para começar com Aprendizagem de Máquina.''

Gareth James, professor de Ciência de Dados e Operações na University of Southern California, e coautor do best-seller An Introduction to Statistical Learning, with Applications in R: "Este livro é um manual compacto de "como implementar ciência de dados", e eu prevejo que se tornará um recurso para acadêmicos e profissionais. Com 100 páginas (ou um pouco mais), o livro é curto o suficiente para ser lido de uma vez. E ainda, apesar do tamanho,ele cobre todas as principais abordagens de Aprendizagem de Máquina, desde a classificação linear e regressão logística, até máquinas modernas de vetores de suporte, aprendizagem de máquina profunda ("deep learning"), "boosting", e florestas aleatórias ("random forests").

Other Formats: Paperback

The Hundred-Page Machine Learning Book en français (French Edition) Aug 2, 2019

by Andriy Burkov , Michel Lutz

( 20 )

$30.95

L'édition française du best-seller The Hundred-Page Machine Learning Book de Andriy Burkov.

Peter Norvig, directeur de recherche chez Google, co-auteur de AIMA, le manuel d'IA le plus populaire au monde: "Burkov a entrepris une tâche très utile, mais incroyablement difficile, de réduire l’apprentissage machine à 100 pages. Il réussit bien à choisir les sujets - à la fois théoriques et pratiques - qui seront utiles aux praticiens, et pour le lecteur qui comprend que ce sont les 100 premières (ou en réalité 150) pages que vous lirez, et non les dernières, constitue une solide introduction dan le domaine."

Aurélien Géron, ingénieur principal en intelligence artificielle, auteur du best-seller Hands-on Machine Learning With Scikit-learn, Keras, and Tensorflow: "L'ampleur des sujets couverts par le livre est incroyable pour seulement 100 pages (plus quelques pages de bonus!). Burkov n'hésite pas d'entrer dans des équations mathématiques: c’est une chose que les livres courts oublient généralement. J’ai vraiment aimé la façon dont l’auteur explique les concepts de base en quelques mots seulement. Ce livre peut être très utile pour les nouveaux venus sur le terrain, ainsi que pour les anciens qui peuvent tirer profit d’une telle vision du domaine".

Karolis Urbonas, Head of Data Science, Amazon: “Une excellente introduction à l’apprentissage machine par un praticien de renommée mondiale.”

Chao Han, VP, Head of R&D, Lucidworks: “J’aurais aimé avoir un tel livre lorsque j’étais étudiant en statistiques et que je voulais apprendre l’apprentissage machine.”Sujeet Varakhedi, Head of Engineering, eBay: “Le livre d’Andriy est fantastique, il va droit au but et permet de rentrer dans le sujet à la vitesse grand V dès la première page.”

Deepak Agarwal, VP of Artificial Intelligence, LinkedIn: “Un livre merveilleux pour les ingénieurs qui veulent incorporer de l’apprentissage machine dans leur travail quotidien sans nécessairement y consacrer beaucoup de temps.”

Vincent Pollet, Head of Research, Nuance: “Une excellente lecture pour débuter en apprentissage machine."

Other Formats: Paperback

The Hundred-Page Machine Learning Book in italiano (Italian Edition) Feb 23, 2020

by Andriy Burkov , Marco Dieterich , Angelo Basile

( 1 )

$37.49

L'edizione italiana del best-seller The Hundred-Machine Learning Book di Andriy Burkov.

Peter Norvig, direttore della ricerca presso Google, coautore di AIMA, il manuale di intelligenza artificiale più popolare al mondo: "Burkov ha intrapreso un compito molto utile ma incredibilmente difficile nel ridurre tutto il machine learning a 100 pagine. Riesce a scegliere bene gli argomenti - sia teorici che pratici - che saranno utili ai professionisti, e al lettore che capisce che queste sono solo le prime 100 (o in realtà 150) pagine da leggere, e non le ultime, fornisce una solida introduzione al campo."

Aurélien Géron, Senior AI Engineer, autore del bestseller Hands-On Machine Learning with Scikit-Learn and TensorFlow: "Per un libro di sole 100 pagine (più alcune pagine bonus!) l'ampiezza degli argomenti trattati è sorprendente. Burkov non esita ad entrare nei dettagli delle equazioni matematiche che solitamente restano fuori dai libri brevi. Ho apprezzato molto la capacità dell’autore di spiegare i concetti chiave in poche parole. Il libro sarà molto utile sia ai principianti che ai professionisti più smaliziati: entrambi avranno molto da apprendere da una visione così ampia del campo."

Karolis Urbonas, Head of Data Science presso Amazon: "Un’ottima introduzione all’apprendimento automatico da parte di un professionista di livello mondiale."

Chao Han, VP, Head of R&D presso Lucidworks: "Vorrei che un libro del genere fosse esistito quando ero uno studente di
statistica che cercava di imparare l’apprendimento automatico."

Sujeet Varakhedi, Head of Engineering presso eBay: "Nel suo libro Andriy fa un lavoro fantastico nel tagliare il superfluo, scendendo
in pista alla massima velocità già dalla prima pagina.''

Deepak Agarwal, VP of Artificial Intelligence presso LinkedIn: "Un libro meraviglioso per gli ingegneri che vogliono incorporare l’AI nel loro
lavoro quotidiano senza spenderci necessariamente una quantità di tempo enorme.''

Vincent Pollet, Head of Research presso Nuance: "Un’ottima lettura per cominciare a conoscere l’apprendimento automatico.''

Gareth James, Professore di Data Sciences and Operations presso la University of
Southern California, co-autore del libro best-seller An Introduction to Statistical Learning, with Applications in R: "Questo è un manuale compatto su “come fare la scienza dei dati” e prevedo che diventerà una risorsa per gli accademici e i professionisti. Con le sue 100 pagine (o poco più), il libro è abbastanza corto da poter essere letto in una sola sessione. Tuttavia, nonostante la sua lunghezza, copre tutti i principali approcci dell’apprendimento automatico, che vanno dalle classiche regressioni lineari e logistiche, fino ai moderni sistemi di support vector machine, apprendimento profondo, boosting e foreste casuali. Inoltre, non mancano i dettagli sui vari approcci e il lettore interessato può ottenere ulteriori informazioni su qualsiasi metodo tramite l’innovativo manuale di accompagnamento della pagina wiki.

Other Formats: Paperback

Machine Learning kompakt: Alles, was Sie wissen müssen (German Edition) Jul 1, 2019

by Andriy Burkov

( 11 )

$25.99

Alles, was Sie über Machine Learning wissen müssen, auf nur 200 Seiten
Von Support Vector Machines über Gradient Boosting und tiefe neuronale Netze bis hin zu unüberwachten Lernmethoden
Zahlreiche Tipps und Empfehlungen für den praktischen Einsatz

Sie möchten Machine Learning verstehen und dafür nicht unendlich viel Zeit aufwenden und Hunderte von Seiten lesen? Dann ist dieses Buch das richtige für Sie.

Auf 200 Seiten bringt Andriy Burkov die wichtigsten Begriffe, Konzepte und Algorithmen des Machine Learnings auf den Punkt. Dabei vermittelt er nicht nur alle notwendigen theoretischen Grundlagen, sondern geht auch auf die praktische Anwendung der einzelnen Verfahren ein, ohne dabei die zugrundeliegenden mathematischen Gleichungen außer Acht zu lassen.

Dieses Buch bietet einen leicht zugänglichen, programmiersprachenunabhängigen und trotz seiner Kürze umfassenden Einstieg ins Machine Learning.

Aus dem Inhalt:

Notation und mathematische Grundlagen
Überwachtes, teilüberwachtes und unüberwachtes Lernen
Grundlegende Lernalgorithmen:

Lineare und logistische Regression
Entscheidungsbäume
Support Vector Machines
k-Nearest-Neighbors

Optimierung mittels Gradientenabstieg
Merkmalserstellung und Handhabung fehlender Merkmale
Auswahl des passenden Lernalgorithmus
Bias, Varianz und das Problem der Unter- und Überanpassung
Regularisierung, Bewertung eines Modells und Abstimmung der Hyperparameter
Deep Learning mit CNNs, RNNs und Autoencodern
Multi-Class-, One-Class- und Multi-Label-Klassifikation
Ensemble Learning
Clustering, Dimensionsreduktion und Erkennen von Ausreißern
Selbstüberwachtes Lernen
Wort-Embeddings, One-Shot und Zero-Shot Learning

Stimmen zum Buch:

»Burkov hat sich der äußerst nützlichen, aber unglaublich schwierigen Aufgabe angenommen, fast das gesamte Machine Learning auf 200 Seiten zusammenzufassen. Die Auswahl der Themen aus Theorie und Praxis ist gelungen und wird sich für Praktiker als nützlich erweisen. Das Buch bietet Lesern eine solide Einführung in das Fachgebiet.«
— Peter Norvig, Forschungsdirektor bei Google

»Der Umfang der Themen, die das Buch auf 200 Seiten behandelt, ist verblüffend. […] Wie der Autor die Kernkonzepte mit einigen wenigen Worten erklärt, gefällt mir ausnehmend gut. Das Buch wird nicht nur für Einsteiger sehr nützlich sein, sondern auch für alte Hasen, die von einer so breiten Sicht auf das Fachgebiet nur profitieren können.«
— Aurélien Géron, Senior Artificial Intelligence Engineer

»Ich wünschte, es hätte ein solches Buch gegeben, als ich mich als Student der Statistik mit Machine Learning beschäftigt habe.«
— Chao Han, Vizepräsident, Leiter Forschung und Entwicklung bei Lucidworks

Other Formats: Perfect Paperback

More Information

Are you an author? Visit Author Central to change your photo, edit your biography, and more

See Author Pages Frequently Asked Questions

Anything else? Provide feedback about this page

Similar authors to follow

About Andriy Burkov

Customers Also Bought Items By

Are you an author?

Author Updates

More Information