All about Artificial Intelligence and Machine Learning for Banking, Finance and Trading
Arificial Intelligence and Machine Learning for Finance and Banks
When you get started with machine learning, you learn to use linear regression to predict numeric values and logistic regression to predict binary variables. You then learn several other popular methods: Nearest neighbors, support vector ...
Predicting gradients for given shares Source
Time Series Forecasting methods including Simple Moving Average, Linear Regression, k-Nearest Neighbors, Auto ARIMA, Prophet, Long Short Term Memory Source
Using Time Series Models to Forecast Cryptocurrency Trends Source
Right around the time you get your first basic regression or classification model going, it will at least cross your mind. The vast piles of time series data, coupled with the possibility of retiring young ...
Stocks and Machine Learning — a combination made in heaven. But are things as easy as they appear to be? Source
Stock prediction is a difficult task because the data generated is enormous and is highly non-linear. Modeling such dynamical data require effective modeling technique which can analyze the hidden patterns and underlying dynamics. Neural network ...
This project is loosely based on a research paper titled “Algorithmic Financial Trading with Deep Convolutional Neural Networks: Time Series to Image Conversion Approach”. Source
In this tutorial, I’m going to show how to use Ray with TensorTrade (TT) in order to create a profitable algorithm on a predictable sine curve. You may be asking yourself, why use something so ...