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How To Use RNNs and Time Series Data for Forecasting Stock Prices

How To Use RNNs and Time Series Data for Forecasting Stock Prices

January 9, 2019 | Ai driven investment strategies, machine learning, neural networks, quantitative analysis,

How to Use Time Series Data and RNNs To Forecast Stock Prices. It’s important to configure deep net infrastructure to accommodate time series data.

Applying Deep Reinforcement Learning to Trading

Applying Deep Reinforcement Learning to Trading

January 7, 2019 | Ai driven investment strategies, Alternative Data, deep learning, machine learning, neural networks, Predictive Analytics, Quantitative Investing, tucker balch, Webinar Videos,

Lucena Research Co-Founder Dr. Tucker Balch provides an introduction to machine learning, specifically applying deep reinforcement learning for stock trading.

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How To Use Deep Neural Networks To Forecast Stock Prices

How To Use Deep Neural Networks To Forecast Stock Prices

January 6, 2019 | Ai driven investment strategies, deep learning, forecasting, neural networks, Predictive Analytics, stock market, stock prices, timeseries data,

Erez Katz, CEO and Co-founder of Lucena Research How To Use Deep Neural Networks To Forecast Stock Prices

Forecast Stock Prices Using Convolutional Neural Networks

Forecast Stock Prices Using Convolutional Neural Networks

January 6, 2019 | Company Blog, convolutional neural networks, deep learning, forecasting, investing, investment strategy, neural networks, stock prices, strategy,

Erez Katz, CEO and Co-founder of Lucena Research

How To Forecast Securities Using Neural Networks

How To Forecast Securities Using Neural Networks

January 5, 2019 | Ai driven investment strategies, Alternative Data, neural networks, Predictive Analytics, Quantitative Investing, Webinar Videos,

Forecast Stocks Using Neural Networks There’s been a lot of buzz surrounding machine learning to forecast stock prices using neural networks. In the webinar we will highlight a unique approach to identifying investment opportunities through the use of deep neural networks.…

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