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  1. Machine Learning with Python Tutorial - GeeksforGeeks

  1. Python is one of the most popular languages for Machine Learning (ML) due to its simplicity and powerful libraries like NumPy, Pandas, Scikit-learn, TensorFlow, and PyTorch. Below is a simple example of training a Linear Regression model using scikit-learn.

    # Import required libraries
    import pandas as pd
    from sklearn.model_selection import train_test_split
    from sklearn.linear_model import LinearRegression

    # Sample dataset
    data = {
    'Experience': [1, 2, 3, 4, 5],
    'Salary': [45000, 50000, 60000, 65000, 70000]
    }
    df = pd.DataFrame(data)

    # Features and target
    X = df[['Experience']]
    y = df['Salary']

    # Split into training and testing sets
    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)

    # Create and train the model
    model = LinearRegression()
    model.fit(X_train, y_train)

    # Predict on test data
    predictions = model.predict(X_test)
    print("Predicted Salaries:", predictions)
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    Key Steps in Python ML Syntax

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