In the previous article Neural Network in Practice: Secant Line, we began to discuss applied mathematics in practice. However, this was only a short and quick introduction to the topic. We have seen that the basic mathematical operation to be used is the trigonometric function. And, contrary to what many think, this is not a tangent function but a secant function. Although this may all seem quite confusing at first, you will soon find that everything is much simpler than it seems. Unlike ...
Introducing two innovative portfolio optimization programs designed to revolutionize trading strategies and maximize returns while minimizing risk The first a Python-based solution leverages the power of MetaTrader 5 integration alongside advanced libraries such as pandas Numpy and cvxpy to analyze historical data optimize asset allocation and visualize results with Matplotlib. The second a similar implementation crafted in MQL5 harnesses the native capabilities of the MetaTrader 5 platform offering ...
In this article, we explore a feature selection algorithm introduced in the paper 'Local Feature Selection for Data Classification' by Narges Armanfard, James P. Reilly, and Majid Komeili. This method aims to identify predictive features that are often overlooked by traditional selection techniques due to their limited global utility. We will begin with a general overview of the algorithm, followed by its implementation in Python to create classifier models suitable for export to MetaTrader ...
Machine learning models are very sensitive instruments. In this series of articles, we will pay significantly more attention to how the transformations we apply to our data, affects our model's performance. Likewise, our models are also sensitive to how the relationship between the input and the target is conveyed. This means, we may need to create new features from the data we have at hand, in order for our model to effectively learn. more...
Forecasting plays an important role in time series analysis. Deep models have brought significant improvement in this area. In addition to successfully predicting future values, they also extract abstract representations that can be applied to other tasks such as classification and anomaly detection. The Transformer architecture, which originated in the field of natural language processing (NLP), demonstrated its advantages in computer vision (CV) and is successfully applied in time ...
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