Machine Learning: Natural Language Processing

There is a lot of excitement around the potential of natural language processing (NLP) with machine learning. Some believe that NLP with machine learning will soon be able to automatically generate translations that are as accurate as those produced by human translators. Others believe that NLP with machine learning will be able to create text that is indistinguishable from that written by humans.

The excitement around the potential of NLP with machine learning is largely driven by the recent advances in artificial intelligence (AI). In particular, deep learning algorithms have shown promise in being able to automatically learn high-level representations from data. This has led to significant advances in NLP tasks such as machine translation, question answering, and text generation.

The future of NLP with machine learning is likely to be very exciting. We can expect to see further advances in AI that enable NLP systems to better understand and generate text.

Machine learning helps Natural Language Processing by providing a way to automatically learn and improve from experience. Machine learning algorithms can be used to automatically learn and extract features from data, which can then be used to improve the performance of Natural Language Processing models.

(FYI: The above paragraph was written by AI machine – the Chatbot by OpenAI)

Let’s start with the Introduction.

All files on GitHub: https://github.com/linhhlp/nlp-ml-1