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Author: Admin | 2025-04-28
Leveraging Random Forest, Regression, and KNN for Predicting Cryptocurrency PricesThis repository contains a machine learning project focused on predicting cryptocurrency prices using various algorithms, including Random Forest, Linear Regression, and K-Nearest Neighbors (KNN).DatasetThe dataset used in this project consists of historical cryptocurrency price data and is provided in a CSV format. You can download the dataset directly from this repository.Download the DatasetTo download the dataset, follow these steps:From GitHub Website:Go to the datasets directory in this repository.Click on the dataset CSV file (e.g., cryptocurrency_data.csv).Once the file opens, click on the "Download" button (or right-click on "Raw" and choose "Save Link As...") to save the file to your local machine.Using Git Command Line:Clone the repository:git clone https://github.com/yourusername/crypto-price-prediction.gitNavigate to the datasets directory:cd crypto-price-prediction/datasetsThe dataset CSV file (e.g., cryptocurrency_data.csv) will be available in the datasets directory after cloning.Example Code to Load the DatasetYou can load the CSV dataset into your Python script using pandas as shown below:import pandas as pd# Load the datasetdf = pd.read_csv('datasets/cryptocurrency_data.csv')# Display the first few rows of the datasetprint(df.head())
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