Topic: “Stock Prediction Using Recurrent Neural Network”
Speaker: Weiguang Guan, SHARCNET
Webinar link: SN-Seminars Vidyo room
Deep learning has made breakthroughs in many areas, such as image recognition, speech recognition, language modeling, etc. In this seminar, we will introduce an RNN (Recurrent Neural Network) and demonstrate how to use it to predict trends in the stock market. First, we will focus on a special RNN – LSTM (Long Short-Term Memory) network, which is capable of keeping and making use of long memory of the past to forecast the future trend. Then, I will use S&P 500 index as time series data to show every step of the analysis: from data reformatting to creating a LSTM network, to training and prediction. NOTE: Our goal is to demonstrate how to build/train a LSTM model, not to describe how to develop a practical stock prediction system.
SHARCNET account is not required to attend the webinar. If you don’t have a SHARCNET account, you don’t need to register for the webinar – just follow the webinar link right before the webinar.
Need help attending a webinar? See the SHARCNET Help Wiki.