How do I implement vectorization and normalization in my data processing?

How do I implement vectorization and normalization in my data processing?

Vectorization and normalization are key steps in data preprocessing. Would you like to know about specific libraries or methods?

Yes, what libraries can I use for this?

You can use libraries like NumPy and scikit-learn in Python. NumPy is great for vectorization, while scikit-learn has built-in functions for normalization.

Can you give me an example of how to normalize data using scikit-learn?

Sure! You can use the StandardScaler class from scikit-learn. Here's a quick example: from sklearn.preprocessing import StandardScaler; scaler = StandardScaler(); normalized_data = scaler.fit_transform(data).

What about vectorization? How do I do that?

For vectorization, you can use CountVectorizer or TfidfVectorizer from scikit-learn, depending on your needs. Would you like a code example for that?