Bộ sách luyện thi ETS 2023 LC&RC
199,000₫
299,000₫
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.
