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  • Book Overview & Buying Mastering Clojure Data Analysis
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Mastering Clojure Data Analysis

Mastering Clojure Data Analysis

By : Eric Richard Rochester
4.2 (5)
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Mastering Clojure Data Analysis

Mastering Clojure Data Analysis

4.2 (5)
By: Eric Richard Rochester
Buy this Book

Overview of this book

Table of Contents (17 chapters)
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Mastering Clojure Data Analysis
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Mastering Clojure Data Analysis
Credits
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Credits
About the Author
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About the Author
About the Reviewers
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About the Reviewers
www.PacktPub.com
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www.PacktPub.com
Preface
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Preface
Lock Free Chapter
1
Network Analysis – The Six Degrees of Kevin Bacon
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Network Analysis – The Six Degrees of Kevin Bacon
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Analyzing social networks
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Getting the data
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Understanding graphs
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Implementing the graphs
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Measuring social network graphs
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Visualizing the graph
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Summary
2
GIS Analysis – Mapping Climate Change
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GIS Analysis – Mapping Climate Change
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Understanding GIS
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Mapping the climate change
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Working with map projections
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Working with ArcGIS
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Summary
3
Topic Modeling – Changing Concerns in the State of the Union Addresses
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Topic Modeling – Changing Concerns in the State of the Union Addresses
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Understanding data in the State of Union addresses
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Understanding topic modeling
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Preparing for visualizations
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Setting up the project
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Getting the data
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Summary
4
Classifying UFO Sightings
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Classifying UFO Sightings
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Getting the data
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Extracting the data
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Dealing with messy data
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Visualizing UFO data
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Description
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Topic modeling descriptions
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Hoaxes
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Summary
5
Benford's Law – Detecting Natural Progressions of Numbers
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Benford's Law – Detecting Natural Progressions of Numbers
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Learning about Benford's Law
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Failing Benford's Law
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Case studies
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Summary
6
Sentiment Analysis – Categorizing Hotel Reviews
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Sentiment Analysis – Categorizing Hotel Reviews
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Understanding sentiment analysis
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Getting hotel review data
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Exploring the data
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Preparing the data
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Cross-validating the results
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Calculating error rates
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Using the Weka machine learning library
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Running the experiment
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Examining the results
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Improving the results
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Summary
7
Null Hypothesis Tests – Analyzing Crime Data
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Null Hypothesis Tests – Analyzing Crime Data
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Introducing confirmatory data analysis
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Understanding null hypothesis testing
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Understanding burglary rates
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Exploring the data
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Conducting the experiment
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Interpreting the results
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Summary
8
A/B Testing – Statistical Experiments for the Web
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A/B Testing – Statistical Experiments for the Web
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Defining A/B testing
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Conducting an A/B test
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Summary
9
Analyzing Social Data Participation
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Analyzing Social Data Participation
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Setting up the project
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Summary
10
Modeling Stock Data
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Modeling Stock Data
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Learning about financial data analysis
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Setting up the basics
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Getting prepared with data
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Analyzing the text
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Inspecting the stock prices
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Merging text and stock features
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Analyzing both text and stock features together with neural nets
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Predicting the future
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Taking it with a grain of salt
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Summary
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Index
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Index

Chapter 10. Modeling Stock Data

Automated stock analysis has gotten a lot of press recently. High-frequency trading firms are a flashpoint. People either believe that they're great for the markets and increasing liquidity, or that they're precursors to the apocalypse. Smaller traders have also gotten into the mix in a slower fashion. Some sites, such as Quantopian (https://www.quantopian.com/) and AlgoTrader (http://www.algotrader.ch/) provide services that allow you to create models for automated trading. Many others allow you to use automated analysis to inform your trading decisions.

Whatever your view of this phenomena, it's an area with a lot of data begging to be analyzed. It's also a nice domain in which to experiment with some analysis and machine learning techniques.

For this chapter, we're going to look for relationships between news articles and stock prices in the future.

In the course of this chapter, we will cover the following topics:

  • Learn about financial data analysis

  • Set up...

CONTINUE READING
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Tech Concepts
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Programming languages
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Mastering Clojure Data Analysis
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