Doing Data Science

Main
Mathematics
Doing Data Science

Doing Data Science

Cathy O'Neil, Rachel Schutt

4.0 / 5.0

คุณชอบหนังสือเล่มนี้มากแค่ไหน

คุณภาพของไฟล์เป็นอย่างไรบ้าง

ดาวน์โหลดหนังสือเพื่อประเมินคุณภาพของไฟล์

คุณภาพของไฟล์ที่คุณดาวน์โหลดมาเป็นอย่างไรบ้าง

A guide to the usefulness of data science covers such topics as algorithms, logistic regression, financial modeling, data visualization, and data engineering.

หมวดหมู่:

ปี:

2013

ฉบับพิมพ์ครั้งที่:

1st

สำนักพิมพ์:

O'Reilly Media

ภาษา:

english

จำนวนหน้า:

375

ISBN 10:

1449358659

ISBN 13:

9781449358655

ไฟล์:

PDF, 27.07 MB

IPFS:

,

english, 2013

อ่านออนไลน์

กำลังแปลงเป็น อยู่

การแปลงเป็น ล้มเหลว

คุณอาจสนใจ

Carl Shan, Max Song, Henry Wang, And William Chen — 120 real data science interview questions

Roger D. Peng, Elizabeth Matsui — The Art of Data Science: A Guide for Anyone Who Works with Data

Andrew Oleksy — Data Science with R A Step By Step Guide With Visual Illustrations and Examples

Vamsee Puligadda — 500 Data Science Interview Questions and Answers

Avrim Blum, John Hopcroft, Ravindran Kannan — Foundations of Data Science

Andrew Park — Data Science for Beginners: 4 Books in 1: Python Programming, Data Analysis, Machine Learning. A Complete Overview to Master The Art of Data Science From Scratch Using Python for Business

John D. Kelleher, Brendan Tierney — Data Science

Norman S. Matloff — Probability and Statistics for Data Science: Math + R + Data

Charles Wheelan — Naked Statistics: Stripping the Dread from the Data

Andrew Gelman, Jennifer Hill — Data Analysis Using Regression and Multilevel/Hierarchical Models

Cathy O’Neil — Weapons of Math Destruction

Anthony Molinaro — SQL Cookbook

Dawn Griffiths — Head First Statistics

Carl Shan, Henry Wang, William Chen; Max Song — The Data Science Handbook

Hadrien Jean — Essential Math for Data Science: Take Control of Your Data with Fundamental Calculus, Linear Algebra, Probability, and Statistics

Chirag Shah — A Hands-On Introduction to Data Science

Field Cady — The Data Science Handbook

Bart Baesens, Veronique Van Vlasselaer, Wouter Verbeke — Fraud analytics using descriptive, predictive, and social network techniques : a guide to data science for fraud detection

Bernard Marr — Big Data in Practice: How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results

John Paul Mueller, Luca Massaron — Python for Data Science, 2nd Edition

Paul D. McNicholas, Peter A. Tait — Data Science with Julia

Drew Conway, John Myles White — Machine Learning for Hackers

Russell Jurney — Agile data science: building data analytics applications with Hadoop

Patil, D. J. — Data jujitsu : the art of turning data into product

Holden Karau, Andy Konwinski, Patrick Wendell, Matei Zaharia — Learning Spark: Lightning-Fast Big Data Analysis

Rachel Schutt, Cathy O'Neil — Doing Data Science: Straight Talk from the Frontline

Garrett Grolemund, Hadley Wickham — Hands-On Programming with R: Write Your Own Functions and Simulations

Foster Provost, Tom Fawcett — Data Science for Business: What You Need to Know About Data Mining and Data-Analytic Thinking

Julie Steele, Noah Iliinsky — Beautiful Visualization: Looking at Data through the Eyes of Experts

Rob Kitchin — The Data Revolution: Big Data, Open Data, Data Infrastructures and Their Consequences

Joel Grus — Data Science from Scratch: First Principles with Python

Tom White — Hadoop: The Definitive Guide, 4th Edition: Storage and Analysis at Internet Scale

Allen B. Downey — Think Stats: Exploratory Data Analysis (Second Edition)

Jake VanderPlas — Python Data Science Handbook

Bill Chambers, Matei Zaharia — Spark: The Definitive Guide: Big Data Processing Made Simple

Scott Murray — Interactive Data Visualization for the Web

Juan Nunez-Iglesias; Stéfan van der Walt; Harriet Dashnow — Elegant Scipy: The Art of Scientific Python

Danyel Fisher, Miriah Meyer — Making Data Visual: A Practical Guide to Using Visualization for Insight

Alex Gorelik — The Enterprise Big Data Lake: Delivering the Promise of Big Data and Data Science

Jeroen Janssens — Data Science at the Command Line

George T. Heineman, Gary Pollice, Stanley Selkow — Algorithms in a Nutshell: A Practical Guide

Peter Bruce, Andrew Bruce — Practical Statistics for Data Scientists: 50 Essential Concepts (Early Release)

คำที่ถูกค้นหาบ่อยที่สุด

บุ๊กลิสต์ที่เกี่ยวข้อง