Part 9/13:
Understanding the probability distribution (via histograms, PMFs, and CDFs).
Using inverse CDF sampling to generate new data points resembling the original data.
Extending this to text, where models can paraphrase, summarize, translate, and even generate entirely new content, thanks to neural networks trained on vast datasets.
The speaker illustrates how, with sufficient data, these methods enable systems to produce realistic numbers, text, and even multimedia outputs by capturing underlying data patterns.
Natural Language Processing in Detail
An exploration of NLP emphasizes understanding and generating human language. It involves multiple components:
- Understanding (NLU): Parsing syntax, semantics, recognizing entities, and intent recognition.