- Machine Learning for Algorithmic Trading
- Stefan Jansen
- 103字
- 2021-06-11 18:47:26
Summary
This chapter introduced the market and fundamental data sources that form the backbone of most trading strategies. You learned about the various ways to access this data and how to preprocess the raw information so that you can begin extracting trading signals using the ML techniques that we will be introducing shortly.
In the next chapter, before moving on to the design and evaluation of trading strategies and the use of ML models, we need to cover alternative datasets that have emerged in recent years and have been a significant driver of the popularity of ML for algorithmic trading.
推薦閱讀
- 嵌入式系統設計教程
- 數字邏輯(第3版)
- 計算機維修與維護技術速成
- Camtasia Studio 8:Advanced Editing and Publishing Techniques
- 計算機組裝與維修技術
- 嵌入式系統中的模擬電路設計
- Spring Cloud微服務架構實戰
- Spring Cloud微服務和分布式系統實踐
- 無蘋果不生活:OS X Mountain Lion 隨身寶典
- Building Machine Learning Systems with Python
- Blender 3D By Example
- Drupal Rules How-to
- Deep Learning with Keras
- 基于STM32的嵌入式系統應用
- Hands-On Explainable AI(XAI) with Python