You’re interested in Natural Language Processing (NLP) in the context of machine learning. NLP is a branch of artificial intelligence focusing on the interaction between computers and humans using natural language. The ultimate objective of NLP is to enable computers to understand, interpret, and generate human languages in a meaningful and helpful way.

Machine learning, intense learning, has dramatically advanced the field of NLP. Techniques like word embeddings, recurrent neural networks (RNNs), transformers, and attention mechanisms have made it possible to create models that can understand and generate human-like text.

Some applications of NLP include:

1. Sentiment Analysis: Determining the sentiment or emotion behind a piece of text.
2. Machine Translation: Automatically translating text between languages.
3. Speech Recognition: Converting spoken language into text.
4. Text Summarization: Producing concise summaries of longer documents or texts.
5. Chatbots: Enabling human-like conversation with machines.

Libraries and tools like NLTK, spaCy, TensorFlow, and PyTorch can help implement NLP models.