Dogecoin Price Prediction with Machine Learning
In this tutorial, I have used a machine-learning algorithm to predict the future price of Dogecoin (a cryptocurrency). I am going to use Python as the programming language.
Dataset Link: Dogecoin.csv
Step-1: Import the necessary Python libraries and explore the given data.
import numpy as np import pandas as pd import matplotlib.pyplot as plt import seaborn as sns from seaborn import regression sns.set() plt.style.use('seaborn-whitegrid') data = pd.read_csv("Dogecoin.csv") print(data.head())
Step-2: Data Visualization
data.dropna() plt.figure(figsize=(10, 4)) plt.title("DogeCoin Price INR") plt.xlabel("Date") plt.ylabel("Close") plt.plot(data["Close"]) plt.show()
Step-3: Applying Machine Learning Model
Note: Install autots library using code “pip install autots”
from autots import AutoTS model = AutoTS(forecast_length=10, frequency='infer', ensemble='simple', drop_data_older_than_periods=200) model = model.fit(data, date_col='Date', value_col='Close', id_col=None) prediction = model.predict() forecast = prediction.forecast print("DogeCoin Price Prediction") print(forecast)
Note: In the last step, it might take more time to achieve the desired result.
which machine learning algorithm used in these program.