They provide numerous examples that show: This repo contains over 150 notebooks that put the concepts, algorithms, and use cases discussed in the book into action. using deep learning models like CNN and RNN with market and alternative data, how to generate synthetic data with generative adversarial networks, and training a trading agent using deep reinforcement learning.how to extract tradeable signals from financial text data like SEC filings, earnings call transcripts or financial news,.the design and evaluation of long-short strategies based on supervised and unsupervised ML algorithms,. ![]()
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