Data Analytics with Hadoop: An Introduction for Data Scientists

✍ Scribed by Benjamin Bengfort, Jenny Kim

Publisher: O’Reilly Media
Year: 2016
Tongue: English
Leaves: 288
Edition: 1
Category: Library

No coin nor oath required. For personal study only.

✦ Subjects

Data Modeling & Design;Databases & Big Data;Computers & Technology;Data Mining;Databases & Big Data;Computers & Technology;Data Processing;Databases & Big Data;Computers & Technology;Structured Design;Software Design, Testing & Engineering;Programming;Computers & Technology;Java;Beginner’s Guides;Reference;Servlets;Programming Languages;Computers & Technology;Database Storage & Design;Computer Science;New, Used & Rental Textbooks;Specialty Boutique;Programming Languages;Computer Science;New, U

📜 SIMILAR VOLUMES

Data Analytics with Hadoop: An Introduct

📁 Data Analytics with Hadoop: An Introduction for Data Scientists

✍ Benjamin Bengfort, Jenny Kim 📂 Library 📅 2016 🏛 O’Reilly Media 🌐 English

Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you'll focus on particular analys

Data analytics with Hadoop: an introduct

📁 Data analytics with Hadoop: an introduction for data scientists

✍ Bengfort, Benjamin;Kim, Jenny 📂 Library 📅 2016 🏛 O'Reilly Media 🌐 English

The age of the data product -- An operating system for big data -- A framework for Python and Hadoop streaming -- In-memory computing with Spark -- Distributed analysis and patterns -- Data mining and warehousing -- Data ingestion -- Analytics with higher-level APIs -- Machine learning -- Summary :

Data Analytics with Hadoop: An Introduct

📁 Data Analytics with Hadoop: An Introduction for Data Scientists

✍ Bengfort, B.; Kim, J. 📂 Library 📅 2016 🏛 O’Reilly Media 🌐 English

<p>Ready to use statistical and machine-learning techniques across large data sets? This practical guide shows you why the Hadoop ecosystem is perfect for the job. Instead of deployment, operations, or software development usually associated with distributed computing, you’ll focus on particular ana

📁 Exploring data : an introduction to data analysis for social scientists

✍ Marsh, Catherine, author 📂 Library 📅 2008 🏛 Cambridge : Polity 🌐 English

xxiii, 304 pages : 25 cm

Data Science for Infectious Disease Data

📁 Data Science for Infectious Disease Data Analytics: An Introduction with R

✍ Lily Wang 📂 Library 📅 2022 🏛 CRC Press/Chapman & Hall 🌐 English

Data Science for Infectious Disease Data Analytics: An Introduction with R provides an overview of modern data science tools and methods that have been developed specifically to analyze infectious disease data. With a quick start guide to epidemiological data visualization and analysis in R, this bo

Statistics for Data Scientists: An Intro

📁 Statistics for Data Scientists: An Introduction to Probability, Statistics, and Data Analysis

✍ Maurits Kaptein, Edwin van den Heuvel 📂 Library 📅 2020 🏛 Springer 🌐 English

<span><p>This book provides an undergraduate introduction to analysing data for data science, computer science, and quantitative social science students. It uniquely combines a hands-on approach to data analysis – supported by numerous real data examples and reusable [R] code – with a rigorous treat