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Clojure for Data Science

You're reading from   Clojure for Data Science Statistics, big data, and machine learning for Clojure programmers

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Product type Paperback
Published in Sep 2015
Publisher
ISBN-13 9781784397180
Length 608 pages
Edition 1st Edition
Languages
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Author (1):
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Henry Garner Henry Garner
Author Profile Icon Henry Garner
Henry Garner
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Toc

Table of Contents (12) Chapters Close

Preface 1. Statistics FREE CHAPTER 2. Inference 3. Correlation 4. Classification 5. Big Data 6. Clustering 7. Recommender Systems 8. Network Analysis 9. Time Series 10. Visualization Index

Index

A

  • A* algorithm
    • URL / Finding the shortest path
  • Acbracad library
    • URL / Distributed unique IDs with Hadoop
  • AcmeContent
    • about / Introducing AcmeContent
    • sample code / Download the sample code
  • acyclic / Visualizing graphs with Loom
  • Adaptive Boosting (AdaBoost) / Bagging and boosting
  • Akaike Information Criterion (AIC)
    • models, identifying / Identifying better models with Akaike Information Criterion
    • about / Identifying better models with Akaike Information Criterion
  • ALS
    • movie recommendations / Movie recommendations with alternating least squares
    • using, with Spark / ALS with Spark and MLlib
    • using, with MLlib / ALS with Spark and MLlib
    • used, for making predictions / Making predictions with ALS
    • evaluating / Evaluating ALS
  • Anscombe's Quartet / The importance of visualizations
  • Apache Commons Math
    • about / Estimating the maximum likelihood, Nelder-Mead optimization with Apache Commons Math
    • URL / Estimating the...
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