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.