Machine learning and big data with kdb+/q /
"The book will start with an examination of the foundations of kdb+/q and will proceed to consider the practicalities of dealing with real high-frequency data, and then demonstrate how kdb+/q can be used to solve econometric problems of practical importance. The exploratory journey of the langu...
| Main Authors: | , , , |
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| Format: | eBook |
| Language: | English |
| Published: |
Chichester, West Sussex, United Kingdom :
John Wiley & Sons, Ltd.,
2020.
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| Series: | Wiley finance series.
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| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
Table of Contents:
- Fundamentals of the q programming language
- Dictionaries and tables : the q fundamentals
- Functions
- Editors and other tools
- Debugging q code
- Splayed and partitioned tables
- Joins
- Parallelisation
- Data cleaning and filtering
- Parse trees
- A few use cases
- Basic overview of statistics
- Linear regression
- Time series econometrics
- Fourier transform
- Eigensystem and PCA
- Outlier detection
- Simulating asset prices
- Basic principles of machine learning
- Linear regression with regularisation
- Nearest neighbours
- Neural networks
- AdaBoost with stumps
- Trees
- Forests
- Unsupervised machine learning : the Apriori algorithm
- Processing information
- Towards AI : Monte Carlo tree search
- Econophysics : the agent-based computational models
- Epilogue: