Hands-On Machine Learning for Algorithmic Trading sách

Giới thiệu Hands-On Machine Learning for Algorithmic Trading sách

Sách keo gáy, Bìa mềm

Thể loại:Computers - Computer Business & Culture

Năm:2018

Ngôn ngữ:english

Trang: 503

Explore effective trading strategies in real-world markets using NumPy, spaCy, pandas, scikit-learn, and Keras Key Features. Implement machine learning algorithms to build, train, and validate algorithmic models. Create your own algorithmic design process to apply probabilistic machine learning approaches to trading decisions. Develop neural networks for algorithmic trading to perform time series forecasting and smart analytics. Book Description The explosive growth of digital data has boosted the demand for expertise in trading strategies that use machine learning (ML). This book enables you to use a broad range of supervised and unsupervised algorithms to extract signals from a wide variety of data sources and create powerful investment strategies. This book shows how to access market, fundamental, and alternative data via API or web scraping and offers a framework to evaluate alternative data. You'll practice the ML workflow from model design, loss metric definition, and parameter tuning to performance evaluation in a time series context. You will understand ML algorithms such as Bayesian and ensemble methods and manifold learning, and will know how to train and tune these models using pandas, statsmodels, sklearn, PyMC3, xgboost, lightgbm, and catboost. This book also teaches you how to extract features from text data using spaCy, classify news and assign sentiment scores, and to use gensim to model topics and learn word embeddings from financial reports.