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Author: Admin | 2025-04-28
In this blog post, we delve into cryptocurrency price prediction using CoinGecko API and machine learning – the ability to learn patterns from data and make informed predictions. We’ll be leveraging CoinGecko API to fetch historical and current crypto market data, which will serve as the foundation for our machine learning model. Trained on this data, our model will then predict future cryptocurrency prices, providing valuable insights for investment strategies and market trend analysis.Disclaimer: While this guide covers machine learning techniques for crypto price prediction, any use or reliance on our content is solely at your own risk and discretion. Do conduct your own research, review, analyze and verify our content before relying on them. Trading is a highly risky activity that can lead to major losses, please therefore consult your financial advisor before making any decisions.Level of FunctionalityWe'll first examine the key functionalities of our Python program: Fetching Data: The program fetches real-time and historical data from the CoinGecko API. This includes the current market data, historical data, and OHLC (Open, High, Low, Close) data for a specific coin. Data Processing: The program processes the fetched data to prepare it for the machine learning model. This includes selecting relevant features, scaling the data, and formatting it into the appropriate shape. Machine Learning Model: The program uses a Linear Regression model from the Scikit-learn library to learn from the processed data. Price Prediction: The program uses the trained model to predict future prices of the selected cryptocurrency. Displaying Predictions: The
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