Our focus lies in leveraging computer vision algorithms to process and interpret visual data, such as candlestick charts, in real-time. By extracting meaningful patterns, trends, and anomalies from these visual representations, we aim to develop predictive models that can assist in making informed trading decisions.
Could you describe what the question is and how it’s related to PyTorch, please?
How can PyTorch be utilized in the development of computer vision algorithms for algorithmic trading?
I’m curious about leveraging CNNs to develop a visual learning bot capable of analyzing candlestick charts. The goal is to extend its capabilities to live charts.