AI-based algorithm for recommending cryptocurrencies

describe what can people use it for, or how it makes existing tasks easier/safer e.t.c (markdown supported)

The problem it solves

tell us about any specific bug or hurdle you ran into while building this project. how did you get over it? (markdown supported)

Challenges we ran into

EXECUTE-3.0

Google Colab

Python

Jupyter Notebook

support vector machines

Naive bayes

CryptoSlayer

We are embarking on the development of an innovative cryptocurrency trading bot, leveraging the Kraken API for real-time market data. Our approach integrates machine learning to discern market trends from historical data, enabling the identification of optimal strategies and indicators.

The trading bot will undergo simulated trading runs on a dedicated server, mimicking live market conditions. Throughout these simulated runs, machine learning algorithms will assess the appropriateness of entry and exit points, enhancing the bot's decision-making capabilities.
The current trading strategy encompasses the core strategy and a machine learning algorithm for entry and exit determinations. Critical to future success is the inclusion of robust risk management practices, encompassing position sizing, stop-losses, take-profits, and trade diversification.

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MoonLight

CryptoSlayer

Utilizing Machine Learning for Market Analysis

The problem CryptoSlayer solves

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