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Basics of NumPy NumPy is a Python library for numerical computations. It provides support for arrays, matrices, and various mathematical operations. Key functions: np.array() - Creates an array. np.mean(), np.median(), np.std() - Statistical calculations. np.linspace() and np.arange() - Create sequences. np.dot() - Matrix multiplication. --- Basics of Pandas Pandas is a library for data manipulation and analysis. Two main structures: Series: One-dimensional data. DataFrame: Two-dimensional, like a table. Key functions: pd.read_csv() - Reads a CSV file. df.head() - Displays the first rows. df.describe() - Summary statistics. df.isnull() - Detects missing values. --- Feature Scaling Adjusts the scale of features to make them comparable. Techniques: Standardization: (x - mean) / std_dev Normalization: (x - min) / (max - min) --- Principal Component Analysis (PCA) and LDA PCA: Reduces dimensionality by finding components that explain variance. LDA: Linear Discriminant Analysis focuses on m...