Menu

Szukaj

Zamknij

Zaloguj się

Biblioteka

0,00 zł (0)

Koszyk

ODBIERZ TWÓJ BONUS :: »

15 Math Concepts Every Data Scientist Should Know. Understand and learn how to apply the math behind data science algorithms David Hoyle

Język publikacji: 1
15 Math Concepts Every Data Scientist Should Know. Understand and learn how to apply the math behind data science algorithms David Hoyle - okladka książki

15 Math Concepts Every Data Scientist Should Know. Understand and learn how to apply the math behind data science algorithms David Hoyle - okladka książki

Autor:
David Hoyle
Serie wydawnicze:
Essentials
Wydawnictwo:
Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
Ocena:
Bądź pierwszym, który oceni tę książkę
Stron:
510
Dostępne formaty:
     PDF
     ePub

Ebook 29,90 zł najniższa cena z 30 dni

129,00 zł (-10%)
116,10 zł

Dodaj do koszyka lub Kup na prezent Kup 1-kliknięciem

29,90 zł najniższa cena z 30 dni

Poleć tę książkę znajomemu Poleć tę książkę znajomemu!!

Przenieś na półkę

Do przechowalni

Prezent last minute w ebookpoint.pl
Zostało Ci na świąteczne zamówienie opcje wysyłki »
Data science combines the power of data with the rigor of scientific methodology, with mathematics providing the tools and frameworks for analysis, algorithm development, and deriving insights. As machine learning algorithms become increasingly complex, a solid grounding in math is crucial for data scientists. David Hoyle, with over 30 years of experience in statistical and mathematical modeling, brings unparalleled industrial expertise to this book, drawing from his work in building predictive models for the world's largest retailers.
Encompassing 15 crucial concepts, this book covers a spectrum of mathematical techniques to help you understand a vast range of data science algorithms and applications. Starting with essential foundational concepts, such as random variables and probability distributions, you’ll learn why data varies, and explore matrices and linear algebra to transform that data. Building upon this foundation, the book spans general intermediate concepts, such as model complexity and network analysis, as well as advanced concepts such as kernel-based learning and information theory. Each concept is illustrated with Python code snippets demonstrating their practical application to solve problems.
By the end of the book, you’ll have the confidence to apply key mathematical concepts to your data science challenges.

Wybrane bestsellery

O autorze książki

David Hoyle has over 30 years' experience in statistical and mathematical modelling. After gaining a degree in Mathematics and Physics and a PhD in Theoretical Physics from the University of Bristol in the UK, he began an academic career that included research at the University of Cambridge and leading his own machine learning research groups at the University of Exeter and the University of Manchester in the UK.
Since 2011 he has worked as a Data Scientist in the private sector, including for Lloyds Banking Group, and AutoTrader UK as Head of Data Science. In 2019 he joined the customer data science company dunnhumby as a Lead Data Scientist, building statistical and machine learning predictive models for the world's largest retailers.

Packt Publishing - inne książki

Zamknij

Przenieś na półkę
Dodano produkt na półkę
Usunięto produkt z półki
Przeniesiono produkt do archiwum
Przeniesiono produkt do biblioteki

Zamknij

Wybierz metodę płatności

Ebook
116,10 zł
Dodaj do koszyka
Sposób płatności
Zabrania się wykorzystania treści strony do celów eksploracji tekstu i danych (TDM), w tym eksploracji w celu szkolenia technologii AI i innych systemów uczenia maszynowego. It is forbidden to use the content of the site for text and data mining (TDM), including mining for training AI technologies and other machine learning systems.