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  1. Machine learning

    Field of study
  2. Machine learning is a subfield of artificial intelligence that enables computers to learn from data and make predictions or decisions without being explicitly programmed. Python is a popular language for machine learning due to its simplicity and the availability of powerful libraries such as Scikit-learn, TensorFlow, and Keras.

    Key Machine Learning Algorithms

    1. Linear Regression

    Linear Regression is used for predicting a continuous-valued attribute. It models the relationship between a dependent variable and one or more independent variables by fitting a linear equation to the observed data.

    from sklearn.linear_model import LinearRegression
    model = LinearRegression()
    model.fit(X_train, y_train)
    predictions = model.predict(X_test)
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    2. Logistic Regression

    Logistic Regression is used for binary classification problems. It models the probability of a binary outcome based on one or more predictor variables.

    from sklearn.linear_model import LogisticRegression
    model = LogisticRegression()
    model.fit(X_train, y_train)
    predictions = model.predict(X_test)
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  1. In this chapter, we will explain why machine learning has become so popular and discuss what kinds of problems can be solved using machine learning. Then, we will show you how to build your first …