Machine learning and big data with kdb+/q
Upgrade your programming language to more effectively handle high-frequency data Machine Learning and Big Data with KDB+/Q offers quants, programmers and algorithmic traders a practical entry into the powerful but non-intuitive kdb+ database and q programming language. Ideally designed to handle the...
| Otros Autores: | , , , |
|---|---|
| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
Chichester, West Sussex, England :
Wiley
[2020]
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| Edición: | 1st edition |
| Colección: | Wiley finance series.
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| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009631482606719 |
Tabla de Contenidos:
- 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: Art.
