Summary
The field of NLP is rapidly evolving, providing an effective means to extract insights from unstructured data such as text. Throughout this chapter, we introduced the field, illustrated a typical task within it, delineated the workflow, discussed pertinent data, and executed model training using embeddings. Additionally, we demonstrated the model evaluation process and showcased its integration into a program that sources headlines from the CryptoPanic API.
It’s worth emphasizing that amassing a substantial volume of data is pivotal for high model accuracy. Nevertheless, in cases where constructing such a model isn’t feasible, alternative solutions are available. We explored one such solution involving the ChatGPT API, which provides access to a text bot trained on a comprehensive corpus of data.
In the subsequent chapter, we will delve into the support that data teams can extend to artistic groups who are seeking to transform their artworks into unique...
