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Deep Learning

Advanced machine learning technique capable of analysing large amounts of data. It is characterised by a multi-layered structure, which makes it possible to find non-linear correspondences between the analysed data and to identify complex patterns that are otherwise difficult to detect.

This technology can understand information at various levels of complexity, significantly improving the ability to make accurate predictions.

Finally, Deep Learning is particularly useful for targets that require the processing of multiple inputs to produce a single output, making it ideal for the complex analysis required in cryptocurrency trading.

Machine Learning

This method is particularly effective in finding linear correlations between input data and desired output. Quick to update with new data, it can quickly learn new information to keep trading strategies up-to-date and responsive to market changes.

LSTM – Long Short Term Memory

LSTM is a type of recurrent neural network that is perfect for time series forecasting. It is excellent at capturing long-term dependencies, which means it can remember important information over long periods of time. Furthermore, LSTM is designed to retain only useful information and autonomously discard useless information, thus improving forecasting efficiency and accuracy.

CNN – Convolutionas Neural Network

CNNs are neural networks capable of learning complex relationships and patterns between data features. They can handle different inputs in terms of size and volume, making them very versatile. Furthermore, CNNs reduce the dimensionality of big data by splitting the data into smaller parts, thus facilitating analysis and processing.

LLM – Large Language Model

LMMs are highly efficient artificial intelligence models for understanding human language. They are capable of processing huge amounts of text and are optimised with
script. These models are particularly useful for extracting specific information from complex discourses, thereby improving the analysis and understanding of textual content.

Reinforcement Learning

Reinforcement Learning is an automatic self-learning method. During the learning process, it introduces penalties to avoid undesirable behaviour, thereby optimising long-term solutions. This approach proves particularly effective in complex situations, where it succeeds in finding optimal strategies through experience.

Markowitz

The Markowitz method is a state-of-the-art technique used to manage investment portfolios. Its main objective is to reduce the risks associated with investments while seeking to maximise portfolio returns. This approach balances risk and return to optimise investment decisions.