Natural Language Processing (NLP)
These are your big, broad tools that do just about anything. This is where good prompting skills come into play.
- Tasks: Understanding, interpreting, and generating human language. This includes:
- Text Summarization: Condensing long texts into shorter, coherent summaries.
- Sentiment Analysis: Determining the emotional tone of text (positive, negative, neutral).
- Chatbots/Conversational AI: Enabling human-like conversations, answering questions, and providing support.
- Translation: Converting text from one language to another.
- Named Entity Recognition (NER): Identifying and classifying entities like names, organizations, and locations.
- Topic Modeling: Discovering abstract topics in a collection of documents.
- Text Generation: Creating new text, like articles, emails, or creative content.
- Text Summarization: Condensing long texts into shorter, coherent summaries.
- Programs/Platforms:
- Google Cloud Natural Language API (GEMINI): Pre-trained models for sentiment analysis, entity extraction, content classification, and more. This is Gemini. This is free all the time and is a pretty good tool. I use it every day.
- OpenAI's GPT series (ChatGPT): Excellent for general text generation, summarization, and conversational AI. There is a free level of this.
- NLTK (Natural Language Toolkit): A popular Python library for research and development in NLP, offering tools for tokenization, stemming, tagging, parsing, and more. Python can do anything, but it is a language you will need to learn first.
- Google Cloud Natural Language API (GEMINI): Pre-trained models for sentiment analysis, entity extraction, content classification, and more. This is Gemini. This is free all the time and is a pretty good tool. I use it every day.