A data scientist at India's prestigious Vellore Institute of Technology has outlined a method for how to purportedly predict crypto prices in real-time using a Long Short-Term Memory (LSTM) neural network. In a blog post published on Dec. 2, researcher Abinhav Sagar demonstrated a four-step process for how to use machine learning technology to forecast prices in a sector he purported is "relatively unpredictable" as compared with traditional markets. Sagar prefaced his demonstration by noting that while machine learning has achieved some success in predicting stock market prices, its application in the cryptocurrency field has been restricted. In support of this claim, he argued that cryptocurrency prices fluctuate in accordance with fast-paced technological developments, as well as economic, security and political factors. Sagar's four-step proposed method involves 1) collecting real-time cryptocurrency data; 2) preparing the data for neural network training; 3) testing the prediction using the LSTM neural network; 4) visualizing the results of the prediction.