How can I get started with machine learning using Scikit-Learn?

How can I get started with machine learning using Scikit-Learn?

To get started with machine learning using Scikit-Learn, first install the library using pip. Then, familiarize yourself with basic concepts like datasets, models, and training.

What are some common algorithms I can use with Scikit-Learn?

Scikit-Learn offers various algorithms, including linear regression, decision trees, and support vector machines. Each has its own use cases.

Can you show me a simple example of using linear regression?

Sure! Here's a basic example:

from sklearn.linear_model import LinearRegression
import numpy as np

# Sample data
X = np.array([[1], [2], [3], [4]])
y = np.array([2, 3, 5, 7])

# Create model
model = LinearRegression()
model.fit(X, y)

# Make a prediction
prediction = model.predict([[5]])
print(prediction)

What resources do you recommend for learning more about Scikit-Learn?

I recommend checking out the official Scikit-Learn documentation, online courses on platforms like Coursera, and books like 'Hands-On Machine Learning with Scikit-Learn'.