Stock Market Prediction is about developing models to predict the further development of a financial asset such as, a stock. There are different approaches to this. In classical machine learning, a prediction model is trained on the basis of historical data in the hope that this will provide information about future developments.
Affinity propagation is an unsupervised clustering technique that stands out from other clustering approaches by its capacity to determine the number of clusters in a dataset. This tutorial demonstrates this capacity by applying the technique to analyze the crypto market structure. We perform a cluster analysis of historical prices of … Read more
Neural networks can generate various outputs, which is especially useful in time-series forecasting to forecast longer periods. In time series regression, the number of neurons in the final output layer determines how many steps in a time series the model can predict. Models with one output return single-step forecasts. Models … Read more
This tutorial develops a Twitter bot in Python that will generate automated trading signals. The bot will pull real-time price data on various cryptocurrencies (Bitcoin, Ethereum, Doge, etc.) from the crypto exchange Gate.io and analyze it using predefined rules. Every time the bot detects a relevant change in prices, it … Read more
