Python Code Machine Learning on Natural Language Sentences

Описание: The Python implementation of machine learning on natural language sentences demonstrates how computers can process and interpret human language. Using libraries such as scikit-learn, NLTK, or spaCy, sentences are first tokenized and converted into numerical features through techniques like TF-IDF or word embeddings. These features are then fed into models such as Naive Bayes, SVM, or neural networks to perform tasks like sentiment analysis, intent detection, or text classification. This pipeline showcases how machines learn from text data to generate meaningful insights and human-like understanding.