Statistics, big data, and machine learning for Clojure programmers
Key Features
Book Description
What you will learn
- Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with confidence
- Implement the core machine learning techniques of regression, classification, clustering and recommendation
- Understand the importance of the value of simple statistics and distributions in exploratory data analysis
- Scale algorithms to websized datasets efficiently using distributed programming models on Hadoop and Spark
- Apply suitable analytic approaches for text, graph, and time series data
- Interpret the terminology that you will encounter in technical papers
- Import libraries from other JVM languages such as Java and Scala
- Communicate your findings clearly and convincingly to nontechnical colleagues
Who this book is for
Table of Contents
- Beginning Data Analysis with Clojure
- Statistical Inference
- Correlations
- Finding Correlations in Big Data
- Labeling Things
- Making Predictions and Spotting Outliers
- Recommender Systems
- Hierarchical and Graph Data
- Integrating into Production Systems
- Into Production
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