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Questions and Answers
What is the main focus of this course?
What is the main focus of this course?
- Using prior knowledge and reasoning
- Pattern matching with rules
- Text as output
- Taking text as input (correct)
What is an example of an application that uses text as input and output?
What is an example of an application that uses text as input and output?
- Assistants (e.g. Siri, Alexa) (correct)
- Documents
- News Aggregation
- Medical records
What is NOT a name for this field of computer science?
What is NOT a name for this field of computer science?
- Machine Learning (correct)
- Text Analytics
- Natural Language Processing (NLP)
- Computational linguistics
What is an example of a text input?
What is an example of a text input?
What makes language more complex than just following rules?
What makes language more complex than just following rules?
What is an example of a task that can be achieved with text as input?
What is an example of a task that can be achieved with text as input?
What is NOT an application of using text as input?
What is NOT an application of using text as input?
What is an example of a source of text input?
What is an example of a source of text input?
What is the benefit of new CPUs and GPUs in the field of Text as Data?
What is the benefit of new CPUs and GPUs in the field of Text as Data?
What is a characteristic of the ELMo and BERT deep learning approaches?
What is a characteristic of the ELMo and BERT deep learning approaches?
What is an example of a high-profile product that uses advanced language models?
What is an example of a high-profile product that uses advanced language models?
What is a way that language models are typically trained?
What is a way that language models are typically trained?
What is a benefit of the internet for language researchers?
What is a benefit of the internet for language researchers?
What is an example of a creative application of advanced language models?
What is an example of a creative application of advanced language models?
What is a current research area that building with linguistics research is tied to?
What is a current research area that building with linguistics research is tied to?
What is a task that language models are typically trained to perform?
What is a task that language models are typically trained to perform?
What is a key characteristic of transformer-based models in the context of language understanding?
What is a key characteristic of transformer-based models in the context of language understanding?
What is a concern related to bigger language models?
What is a concern related to bigger language models?
What should you be cautious of when it comes to claims of language models 'understanding' text?
What should you be cautious of when it comes to claims of language models 'understanding' text?
What is a recent development in the field of text as data?
What is a recent development in the field of text as data?
What is an application of language models?
What is an application of language models?
What is a characteristic of the field of text as data?
What is a characteristic of the field of text as data?
What is an example of a language model that has shown impressive abilities in text generation?
What is an example of a language model that has shown impressive abilities in text generation?
What is a benefit of language models in terms of input and output?
What is a benefit of language models in terms of input and output?
What is a primary reason why computers need to work with text?
What is a primary reason why computers need to work with text?
Which of these examples best demonstrates text being used as both input and output for a computer?
Which of these examples best demonstrates text being used as both input and output for a computer?
Why is unstructured text data challenging to process?
Why is unstructured text data challenging to process?
What is a key implication of the rapidly growing amount of text data?
What is a key implication of the rapidly growing amount of text data?
Which of the following best describes the use of a language model in the context of text processing?
Which of the following best describes the use of a language model in the context of text processing?
How do Transformer models differ from traditional recurrent neural networks (RNNs) for natural language processing?
How do Transformer models differ from traditional recurrent neural networks (RNNs) for natural language processing?
Which of the following deep learning architectures is commonly used for text generation tasks?
Which of the following deep learning architectures is commonly used for text generation tasks?
What is a key challenge in developing language models that can understand and interpret the meaning of text?
What is a key challenge in developing language models that can understand and interpret the meaning of text?
What is the primary purpose of using bi-grams and tri-grams in text analysis?
What is the primary purpose of using bi-grams and tri-grams in text analysis?
What is a common challenge when splitting text into words during tokenization?
What is a common challenge when splitting text into words during tokenization?
Which of the following best describes stemming in the context of text processing?
Which of the following best describes stemming in the context of text processing?
How do stopwords impact the effectiveness of text analysis?
How do stopwords impact the effectiveness of text analysis?
In which scenario would lemmatization be preferred over stemming?
In which scenario would lemmatization be preferred over stemming?
What is the initial step in a standard text analysis pipeline?
What is the initial step in a standard text analysis pipeline?
Why is it important to use metrics to weigh rarer words more heavily?
Why is it important to use metrics to weigh rarer words more heavily?
What is a significant limitation of character-based analysis in natural language processing?
What is a significant limitation of character-based analysis in natural language processing?
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Study Notes
What is Text as Data?
- Also known as Natural Language Processing (NLP), Computational Linguistics, and Text Analytics
- Involves working with text as input, output, or both
- Text data is unstructured, growing rapidly, and hard to process
Text as Input
- Examples: documents, tweets, voice commands, search queries, web pages, medical records, books
- Applications: news aggregation, search tools, email suggestions
Text as Output
- Examples: basic text output with rules (e.g., generating numbers with rules), advanced text output (e.g., creative writing)
- Applications: assistants (e.g., Siri, Alexa), machine translation, email suggestions, text adventure games
Text as Data History and Future
- Built on linguistics research (e.g., how language works, how we learn language)
- Tied to computational performance (e.g., new CPUs and GPUs enable advances)
- The internet provides an incredible source of example text
- Deep learning is changing the approach, making it a fast-moving field
New Language Systems and Abilities
- Trained by asking them to complete a sentence
- Developed models like ELMo and BERT, which can succeed at several different problems
- Can find similar documents (e.g., document similarity task)
Course Introduction
- Why computers need to work with text: humans interact with language, and language can be represented as text
- Overview of the course: what we will learn, practicalities (e.g., labs, assessments)
- Importance of working with text: text data is growing rapidly, and computers may use text as input, output, or both
Text Data and Deep Learning
- Text data is ever-growing, and we need to work with it
- BERT model showed incredible new abilities
- Deep learning has had a significant impact on the field, with transformers and language models
- However, bigger models come with huge costs (e.g., training, computational, data, environmental)
Summary of Text as Data Introduction
- Computers use text as input and output
- Amount of text data is growing rapidly
- Deep learning has had a significant impact on the field
- Field is very fast-moving
- Importance of being skeptical of AI "understanding" text claims
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