La scienza dei dati è l'area di studio che implica l'estrazione di approfondimenti da grandi quantità di dati mediante l'uso di vari metodi, algoritmi e processi scientifici. Ti aiuta a scoprire modelli nascosti dai dati grezzi. La scienza dei dati è emersa a causa dell'evoluzione delle statistiche matematiche, dell'analisi dei dati e dei big data.
Di seguito è riportato un elenco curato dei 17 migliori libri di Data Science che dovrebbero far parte della libreria per principianti e avanzati di Data Science Learners.
1) Scienza dei dati da zero: primi principi con Python
Data Science from Scratch è un libro scritto da Joel Gurus. Questo libro ti aiuta a imparare la matematica e le statistiche che sono al centro della scienza dei dati. Imparerai anche le abilità di hacking necessarie per iniziare come data scientist.
I libri includono argomenti come implementare vicini k-più vicini, Naïve Bayes, regressione lineare e logistica, alberi decisionali e modelli di clustering. Sarai anche in grado di esplorare l'elaborazione del linguaggio naturale, l'analisi di rete, ecc.
Controlla l'ultimo prezzo e le recensioni degli utenti su Amazon2) Data Science For Dummies
Data Science For Dummies è un libro scritto da Lillian Pierson. Questo libro è ideale per professionisti IT e studenti che desiderano una rapida introduzione a tutte le aree del vasto spazio della scienza dei dati.
Il libro copre argomenti come big data, scienza dei dati e ingegneria dei dati e come tutte queste aree sono combinate a cui offre un grande valore. Imparerai anche tecnologie, linguaggi di programmazione e metodi matematici.
Controlla l'ultimo prezzo e le recensioni degli utenti su Amazon3) Big Data: una rivoluzione che trasformerà il modo in cui viviamo, lavoriamo e pensiamo
Big Data è un libro scritto da Viktor Mayer-Schonberger e Kenneth Cukier. Il libro parla dello sguardo ottimista e pratico alla rivoluzione dei Big Data. Gli autori di questo libro parlano anche di come la tecnologia dei Big Data sia in grado di cambiare le nostre vite e di cosa possiamo fare per proteggerci dai suoi pericoli.
Controlla l'ultimo prezzo e le recensioni degli utenti su Amazon4) Storytelling con i dati: una guida alla visualizzazione dei dati per i professionisti aziendali
Storytelling with data è un libro scritto da Cole Nussbaumer Knaflic. In questo libro imparerai i fondamenti della visualizzazione dei dati e come comunicare in modo efficace con i dati. Le lezioni in questo libro sono principalmente teoriche e offrono molti esempi del mondo reale pronti per l'applicazione immediata al tuo prossimo grafico o presentazione.
Questo libro insegna anche al lettore come possono andare oltre gli strumenti prevedibili per raggiungere la radice dei tuoi dati. Include anche un argomento su come utilizzare i dati per creare una storia coinvolgente e informativa.
Controlla l'ultimo prezzo e le recensioni degli utenti su Amazon5) Progettazione di applicazioni ad alta intensità di dati
Designing Data-Intensive Applications è un libro scritto da Martin Kleppmann. Questo libro aiuta ad apprendere i vantaggi e gli svantaggi di varie tecnologie per l'elaborazione e l'archiviazione dei dati. Questo libro aiuta anche gli ingegneri del software e gli architetti a imparare come sfruttare appieno i dati nelle applicazioni moderne.
Il libro ti aiuta a prendere decisioni informate identificando i punti di forza e di debolezza di diversi strumenti e navigando tra i compromessi tra coerenza, scalabilità, tolleranza agli errori e complessità.
Controlla l'ultimo prezzo e le recensioni degli utenti su Amazon6) Statistiche pratiche per data scientist: 50 concetti essenziali
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.
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