Livrare gratuită pentru comenzile de peste 349 LEI prin Easybox, FAN BOX și Coletăria.

Verifică starea comenzii

Faceți parte dintr-o comunitate de iubitori de cărți din întreaga lume și beneficiați de o mulțime de avantaje Creați-vă un cont gratuit

Transport gratuit la punctele de livrare Pick Up peste 349.00 lei

Packeta 15.00 lei Serviciul de curierat Cargus 28.00 lei Easybox 20.00 lei Punct FAN 16.00 lei Punct DPD 17.00 lei Curier DPD 25.00 lei FAN Courier 25.00 lei

Contact

Cum să cumpăr

Ajutor

Contul meu

▸ Gol :-(

Livrare gratuită pentru comenzile de peste 349 LEI prin Easybox, FAN BOX și Coletăria.

Math for Data Science

Name: Math for Data Science
Brand: Springer, Berlin
SKU: 48207290
Price: 418.23 RON
Availability: InStock
Author: Omar Hijab
ISBN: 9783031897061

Omar Hijab

Limba

engleză

Carte Copertă tare

Codul Libristo: 48207290

Editura Springer, Berlin, noiembrie 2024

Math for Data Science presents the mathematical foundations necessary for studying and working in Da... Descrierea completă

Codul Libristo: 48207290

193 b

418.23 lei

În depozitul extern Expediem în 10-13 zile

Până la 30 de zile pentru returnare

Ar putea de asemenea, să te intereseze

Mathematical Foundations of Data Science Tomas Hrycej

Carte broșată

334.96 lei

No Bullshit Guide to Math and Physics Ivan Savov

Carte broșată

141.17 lei

Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow Aurelien Geron

Carte broșată

374.15 lei

Ancient Magus' Bride: The Silver Yarn (Light Novel) 2 Kore Yamazaki

Carte broșată

64.03 lei

A Dog Named Banana Isis Val

Carte broșată

56.96 lei

The Heart of Roosevelt: An Intimate Life Story of Theodore Roosevelt Wayne Whipple

Carte broșată

178.80 lei

Tarot of the Divine Yoshi Yoshitani

Cărți

81.18 lei

Student Solutions Manual, Chapters 12-16 for Stewart/Clegg/Watson's Multivariable Calculus, 9th James Stewart

Carte broșată

807.98 lei

Strangest Secret Earl Nightingale

Copertă tare

85.55 lei

Leon Spilliaert Anne Adriaens-Pannier

Copertă tare

317.59 lei

Attacking Repertoire for White with 1.d4 Viktor Moskalenko

Carte broșată

162.58 lei

Red Rubber Edmund Dene Morel

Copertă tare

206.56 lei

Fighting Churchill, Appeasing Hitler: Neville Chamberlain, Sir Horace Wilson, & Britain's Plight of Appeasement: 1937-1939 Tim Bouverie

Copertă tare

149.59 lei

Malina Ingeborg Bachmann

Carte broșată

66.01 lei

Victoria Marmot and the Dragon's Rage Virginia McClain

Carte broșată

67.56 lei

Educated Tara Westover

Carte broșată

64.97 lei

All the Words You Need to Know Before You Start School NOT KNOWN

Cărți pliante

74.43 lei

Computational Intelligence in Data Mining Himansu Sekhar Behera

Carte broșată

1 135.77 lei

Letters from Percy Bysshe Shelley to William Godwin Percy B Shelley

Carte broșată

84.61 lei

Sun Rise: A Poet's Guide to Haad Rin and the Full Moon Nathaniel Kostar

Carte broșată

56.96 lei

21st Century Military-Media Relationships: Improving Relations and the Narrative Through Education National Defense University Joint Forces

Carte broșată

71.62 lei

Counting Silly Faces: Numbers Eighty-One to Ninety Michael Richard Craig

Carte broșată

71.41 lei

Classroom Guitar Workbook, Book 1: A guitar method book for schools. Rick J Piche

Carte broșată

81.39 lei

Anti-Jacobin Novels, Part I, Volume 5 W M Verhoeven

Adobe ePub DRM

376.23 lei

Math for Data Science presents the mathematical foundations necessary for studying and working in Data Science. The book is suitable for courses in applied mathematics, business analytics, computer science, data science, and engineering. The text covers the portions of linear algebra, calculus, probability, and statistics prerequisite to Data Science. The highlight of the book is the machine learning chapter, where the results of the previous chapters are applied to neural network training and stochastic gradient descent. Also included in this last chapter are advanced topics such as accelerated gradient descent and logistic regression trainability.

Clear examples are supported with detailed figures and Python code; Jupyter notebooks and supporting files are available on the author's website. More than 380 exercises and nine detailed appendices covering background elementary material are provided to aid understanding. The book begins at a gentle pace, by focusing on two-dimensional datasets. As the text progresses, foundational topics are expanded upon, leading to deeper results at a more advanced level.