Andmeteadus on uurimisvaldkond, mis hõlmab mitmesuguste teaduslike meetodite, algoritmide ja protsesside abil teadmiste ammutamist tohututest andmetest. See aitab teil algandmetest avastada varjatud mustreid. Andmeteadus on tekkinud matemaatilise statistika, andmete analüüsi ja suurandmete arengu tõttu.
Siin on kureeritud nimekiri top 17 andmeteaduste raamatust, mis peaksid kuuluma kõigi algajate ja edasijõudnute andmeteaduste õppijate raamatukogusse.
1) Scratchi andmeteadus: esimesed põhimõtted Pythoniga
Data Science from Scratch on Joel Guruse kirjutatud raamat. See raamat aitab teil õppida matemaatikat ja statistikat, mis on andmeteaduse keskmes. Samuti saate teada häkkimisoskused, mida vajate andmeteadlasena alustamiseks.
Raamatud hõlmavad selliseid teemasid nagu k-lähimate naabrite rakendamine, Naivi Bayes, lineaarne ja logistiline regressioon, otsustuspuud ja klastrite mudelid. Samuti saate uurida loomuliku keele töötlemist, võrgu analüüsi jne.
Kontrollige Amazoni uusimat hinda ja kasutajate ülevaateid2) Andmeteadus mannekeenidele
Data Science For Dummies on Lillian Piersoni kirjutatud raamat. See raamat on ideaalne IT-spetsialistidele ja üliõpilastele, kes soovivad kiiret aabitsat, mis hõlmaks kõiki ulatusliku andmeteaduse ruumi valdkondi.
Raamat käsitleb selliseid teemasid nagu suurandmed, andmeteadus ja andmetehnoloogia ning see, kuidas kõik need valdkonnad on ühendatud, pakkudes suurt väärtust. Samuti saate teada tehnoloogiatest, programmeerimiskeeltest ja matemaatilistest meetoditest.
Kontrollige Amazoni uusimat hinda ja kasutajate ülevaateid3) suured andmed: revolutsioon, mis muudab meie elamise, töötamise ja mõtlemise
Big Data on Viktor Mayer-Schonbergeri ja Kenneth Cukieri kirjutatud raamat. Raamatus räägitakse Big Data revolutsiooni optimistlikust ja praktilisest pilgust. Selle raamatu autorid räägivad ka sellest, kuidas suurandmetehnoloogia suudab muuta meie elu ja mida saame teha, et kaitsta end selle ohtude eest.
Kontrollige Amazoni uusimat hinda ja kasutajate ülevaateid4) Jutustamine andmetega: Andmete visualiseerimise juhend ärispetsialistidele
Jutustamine andmetega on Cole Nussbaumer Knaflici kirjutatud raamat. Selles raamatus saate teada andmete visualiseerimise põhialused ja selle, kuidas andmetega tõhusalt suhelda. Selle raamatu õppetunnid on enamasti teoreetiliselt ja pakuvad palju reaalses maailmas näiteid , mis on kohe teie järgmise graafiku või esitluse jaoks rakendatavad.
See raamat õpetab lugejat ka sellest, kuidas nad saavad teie andmete juureni jõudmiseks minna etteaimatavatest vahenditest kaugemale. See sisaldab ka teemat, kuidas oma andmeid kasutada kaasahaarava ja informatiivse loo loomiseks.
Kontrollige Amazoni uusimat hinda ja kasutajate ülevaateid5) Andmemahukate rakenduste kujundamine
Andmemahukate rakenduste kujundamine on Martin Kleppmanni kirjutatud raamat. See raamat aitab õppida andmete töötlemise ja salvestamise erinevate tehnoloogiate eeliseid ja puudusi. See raamat aitab tarkvarainseneridel ja arhitektidel õppida tundma, kuidas andmeid kaasaegsetes rakendustes täielikult kasutada.
Raamat aitab teil teha teadlikke otsuseid, tuvastades erinevate tööriistade tugevad ja nõrgad küljed ning liikudes kompromissides järjepidevuse, mastaapsuse, rikketaluvuse ja keerukuse ümber.
Kontrollige Amazoni uusimat hinda ja kasutajate ülevaateid6) Praktiline statistika andmeteadlastele: 50 olulist mõistet
Practical Statistics for Data Scientists is a book written by Peter Bruce (Author), Andrew Bruce. This book explains how to apply various statistical methods to data science, and gives you advice on what's important and what's not.
This book is an easy-to-use data science reference book if you're familiar with the R programming and have some knowledge of statistics.
Check Latest Price and User Reviews on Amazon7) Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data
Data Science and Big Data Analytics is a book published by EMC education service. This book covers the breadth of activities and methods and tools that data scientists use. The book focuses on concepts, principles, and practical applications.
It applies to any industry and technology environment, and the learning. It is supported and explained with examples that you can replicate using open-source software.
Check Latest Price and User Reviews on Amazon8) Data Science for Business: What You Need to Know about Data Mining and Data-Analytic Thinking
Data Science for business is a book written by known data science experts Foster Provost and Tom Fawcett. This Data science study book introduces the fundamental principles of data science. This study book helps you understand the many data-mining techniques in use today.
You'll also learn how to improve communication between business stakeholders and data scientists. It also helps you understand the data-analytical process and how data science methods able to support business decision-making.
Check Latest Price and User Reviews on Amazon9) Head First Statistics: A Brain-Friendly Guide
Head First Statistics is a book written by Dawn Griffiths. The writer brings this typically dry subject to life, teaching you everything you want and need to know about statistics through a material that is full of puzzles, stories, quizzes, and real-world examples.This book helps you to learn statistics so you can understand key points and use them. The book also covers how to present data visually with charts and plots. Lastly, the book also teaches how you can calculate probability and expectation, etc.
Check Latest Price and User Reviews on Amazon10) R for data science: Import, Tidy, Transform, Visualize, And Model Data
R for Data Science is a book written by Hadley Wickham. It is designed to get you doing data science as quickly as possible.
The book guides you through the steps of importing, exploring, and modeling your data and communicating the results.
In this book, you will get a complete, big-picture understanding of the data science cycle. Apart from the basic tools, you need to manage the details. Each section of this book is paired with exercises to help you practice what you've learned along the way.
Check Latest Price and User Reviews on Amazon11) Hands-On Machine Learning
Hands-On Machine Learning is a Data Science book written by Aurélien Géron. The book helps you learn the concepts and tools for building intelligent systems. You'll learn also learn various techniques, like simple linear regression and progressing to deep neural networks. Each chapter of this book helps you apply what you've learned; all you need is programming experience.
Check Latest Price and User Reviews on Amazon12) Python for Data Analysis: Data Wrangling with Pandas, NumPy, and IPython
Python for Data Analysis is a book written by Wes McKinney. This reference book is full of case studies showing how to solve many commonly faced data analysis problems. In this Data science book, you will learn the latest versions of pandas, NumPy, IPython, and Jupyter.
This reference book is a practical, modern introduction to data science tools in Python. It's an ideal book for analysts new to Python and Python programmers.
Check Latest Price and User Reviews on Amazon13) Introduction to Machine Learning with Python: A Guide for Data Scientists
Machine learning with Python is a book written by Andreas C. Müller (Author), Sarah Guido (Author). In this book, you will learn the steps necessary to create a successful machine-learning application with Python and the sci-kit-learn library.
In this book, you will learn the steps necessary to create a successful machine-learning application with Python and the scikit-learn library. This study material also introduces you to NumPy and matplotlib libraries.
Check Latest Price and User Reviews on Amazon14) Practical Data Science with R
Practical Data Science with R is a book written by Nina Zumel (Author), John Mount (Author), and Jim Porzak. The book explains basic principles without lengthy theoretical details. You will provide the real use cases you'll face as you collect, curate, and analyze the data.
You'll able to apply the R programming language and statistical analysis techniques. The book carefully explained examples based on marketing, BI, and decision support system. The book also covers topic like how to design experiments which is build on predictive models.
Check Latest Price and User Reviews on Amazon15) Thinking with Data
Thinking with data is a book written by Max Sharon. It helps you learn techniques for turning data into knowledge you can use. In this book, you will discover a framework for defining your project. It also includes data you want to collect and how you intend to approach and analyze its results.
This Data Science book also helps you to explore data-specific patterns of reasoning and learn how to build more useful arguments.
Check Latest Price and User Reviews on Amazon16) The Data Science Handbook
The Data Science Handbook is written by Field Cady. It is an ideal reference book for data analysis methodology and big data software tools. The book is ideal for people who want to practice data science but lack the required skill sets.
This Data science book is also an ideal study material for researchers as well as entry-level graduate students. They require to learn real-world analytics and expand their skill set.
Check Latest Price and User Reviews on Amazon17) An Introduction to Statistical Learning
An Introduction to Statistical Learning is a book written by a group of authors like Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshira. This Data Science book presents useful modeling and prediction techniques, along with relevant applications.
The book offers color graphics and real-world examples used to illustrate the methods presented. Each chapter of this book contains a tutorial on implementing the analyses and methods presented in the R language.
Check Latest Price and User Reviews on Amazon