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Practical Data Analysis

You're reading from   Practical Data Analysis Pandas, MongoDB, Apache Spark, and more

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Product type Paperback
Published in Sep 2016
Publisher
ISBN-13 9781785289712
Length 338 pages
Edition 2nd Edition
Languages
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Authors (2):
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Hector Cuesta Hector Cuesta
Author Profile Icon Hector Cuesta
Hector Cuesta
Dr. Sampath Kumar Dr. Sampath Kumar
Author Profile Icon Dr. Sampath Kumar
Dr. Sampath Kumar
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Toc

Table of Contents (16) Chapters Close

Preface 1. Getting Started FREE CHAPTER 2. Preprocessing Data 3. Getting to Grips with Visualization 4. Text Classification 5. Similarity-Based Image Retrieval 6. Simulation of Stock Prices 7. Predicting Gold Prices 8. Working with Support Vector Machines 9. Modeling Infectious Diseases with Cellular Automata 10. Working with Social Graphs 11. Working with Twitter Data 12. Data Processing and Aggregation with MongoDB 13. Working with MapReduce 14. Online Data Analysis with Jupyter and Wakari 15. Understanding Data Processing using Apache Spark

Quantitative analyst


Quantitative finance is an amazing area that applies mathematical models to financial markets; example tasks include algorithmic trading, derivatives pricing, and risk management. This requires people with financial, computer, and analytical skills; this person is called a quantitative analyst or a quant. A quantitative analyst is in charge of proposing testable hypotheses and develops models to uncover hidden patterns. Quantitative finance helps to apply the scientific method to the study of financial markets using simulations like those we used in this chapter, or predictive methods like the ones we will use in Chapter 7, Predicting Gold Prices.

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