5 книжок про великі дані й машинне навчання від Дмитра Білаша

Дмитро Білаш – керуючий партнер компанії Septa, організатор конференції Kyiv Data Spring, співзасновник видання datification.org. Займається впровадженням технологій великих даних і машинного навчання в компанії, а також розробкою machine learning рішень для бізнесу.


1

«Большие данные. Революция, которая изменит то, как мы живем работаем и мыслим»
Віктор Майер-Шенбергер і Кеннет Кук’єр


В інтернеті ви легко знайдете дуже багато містких статей, які чудово розкривають тему даних і машинного навчання. І може виникнути питання: “Навіщо ж витрачати час на книги?”. Але ця робота дійсно варта уваги. Саме цю книгу про великі дані я прочитав першою, вона пробудила інтерес до нової теми і я почав з неї вхід в професію.

“Великі дані. Революція, яка змінить те, як ми живемо працюємо і мислимо”, – найкраща книга для старту, рекомендую її кожному, хто хоче зрозуміти, як працює майбутнє.

2

«Революция в аналитике. Как в эпоху Big Data улучшить ваш бизнес с помощью операционной аналитики»
Білл Френкс


Попри те, що в заголовку є слово “революція”, ця книга про еволюцію – вона про те, у що еволюціонує класична аналітика в бізнес-організаціях. Що таке операційна аналітика? Як використовуються дані для аналітики нового покоління і коли машини почнуть приймати рішення замість нас? Відповіді на всі ці питання ви знайдете в книзі Білла Френкса.

Рекомендую цю книгу фахівцям з аналітики та людям, які вже базово розібралися в тому, як працюють великі дані й машинне навчання.

3

«Верховный алгоритм» Педро Домігос


Захоплива науково-популярна книжка про машинне навчання. Як працюють алгоритми, які самонавчаються і, немов діти, вбирають дані з навколишнього цифрового світу? На що ці алгоритми здатні сьогодні та чому вони навчаться вже завтра? Чи вдасться людству створити справжній штучний інтелект?

Якщо вас цікавлять відповіді на ці питання, рекомендую.

4

«Укрощение больших данных» Біл Френкс


Це вже друга книга Била Френкса в моїй добірці, але що поробиш, якщо він пише цікаво й доречно?

“Приборкання великих даних” – це книжка для управлінців. Рекомендую її middle і топ-менеджерам, які хочуть зробити свій бізнес data-driven, впровадити машинне навчання в роботу компанії та почати приймати рішення на основі даних.

5

«Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Diet»
Eric Siegel и Thomas H. Davenport


Одне з найбільш перспективних напрямків в роботі з даними – це предиктивна аналітика, а простіше кажучи – передбачення майбутнього. Машини вже сьогодні передбачають події: які пости в Facebook будуть цікаві саме вам, який фільм найбільше сподобається конкретному глядачеві, кому варто видати кредит, а кому – відмовити в позиції й багато іншого.

Ця книга розкриває тему предиктивної аналітики на прикладах з життя. Цікаво, що можуть передбачити машини і як їм це вдається? Тоді читайте роботу Еріка Сігеля і Томаса Давенпорта.


Сподобалися книги, які я рекомендую? Додавайте мене в друзі на Facebook – я часто пишу про дані, машинне навчання, майбутнє бізнесу і багато іншого.

Ксеня Різник
Редакторка blog.yakaboo.ua, блогерка в Етажерка. 10 років пишу про книжки (OpenStudy, газета День, gazeta.ua, MediaOsvita, власний блог та блог Yakaboo). Природний для мене стан: читати, розповідати та писати про книжки. Трішки схиблена на сучасній британській літературі, шпигую за лауреатами усіляких премій, найкращих додаю у список "читати негайно"). У вільний від книжок час знайомлюсь із птахами, марную фарби та олівці.
http://ksenyak.wordpress.com

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