"Text without a context, it's just a pretext for whatever you want it to mean."
"Amid a diversity of texts, there is a stable text."
"We're not with this demo recommending that CH expert be applied to Kovac diagnosis we're more using it as a demonstration tool."
"It doesn't say what we think it was saying. What it actually says is much, much, much worse."
"Hidden Gospel fragment suggests multiple authors."
"Visualize the distribution of text lengths using a histogram."
"That is misleading text if I've ever seen it."
"Chat GPT is pretty human-like when it comes to text because by golly it just read a large fraction of the text that we humans at least publicly wrote."
"Sentiment analysis: Sentiment analysis determines the author's feelings about a text, employing natural language processing and text analysis technology."
"...there is no conflict between the two versions of the text when they are interpreted in the fashion proposed here."
"To me, the best way to think about embeddings is on a chart. Text with similar meaning will be plotted together on the chart and those that are dissimilarly far apart."
"P consciously follows the J and E text."
"NLP enables you to analyze text documents, extract key phrases, recognize entities, perform sentiment analysis, interpret spoken language, synthesize speech responses, and translate languages."
"You can use text analysis to analyze text documents and extract key phrases."
"Regular expressions can be used to find patterns in text."
"It could be a really nice way to have feedback and discussion around a piece of text."
"The whole goal of splitting your text is to best prepare it for the task that you actually have at hand."
"Help me understand how this text don't mean what it sounds like it clearly means."
"I want to know what John wrote. I don't think a TR-only advocate can look me in the eye and say I want to know what John wrote, because that's not how they're behaving when they deal with the text."
"So, AI Builder allows you to analyze the overall sentiment of a text and even the sentiment of each sentence."
"This means we can give it a text without knowing the corresponding label."
"The resulting text itself shows fractal-like structures."
"It's important for us to recognize the nature of these texts and to take care in how we approach them."
"Language models can induce a lot of information about experience just by being trained on a lot of text that talks about experience."
"You've raised a generation that does not examine the text, we're trying to find the truth without the text and there is no truth outside of the text."
"Feature representations hold the key to training a powerful neural network. For image data, input pixels form the basis of derivation of these features; for text, it is the word tokens that form the user review sentences, forming the basis for derivation of features."
"What is sentiment analysis? It's a natural language processing technique that allows us to classify text and speech as either positive or negative, subjective or objective."
"If you're interested in doing text analysis and are maybe considering topic modeling as a solution to a problem that you're having, then look no further."
"We're just doing a logistic regression on top of our bag of words representation."
"You can build an inference model that can take raw input text."
"A system has understood where the relationship between a country and its capital is essentially just by reading tons of text."
"It's more important for me to understand what the narrator is doing with the text theologically."
"Analyze the text, look for those themes, those symbols, those motifs."
"By analyzing a real-world text like a newspaper article, you will learn to use English in a way that's relevant and practical."
"We're able to use language models and Foundation models in general to understand very very long spans of text and to create incredibly useful or incredibly tailored incredibly interesting Generations."
"If you get really good at predicting the next sentence in text, you also to some degree have to learn to predict an agent's beliefs, their backgrounds, common knowledge, and what they might do next."
"The Natural Language Toolkit, or NLTK, is one of the most popular natural language processing libraries."
"Chunking is the process of extraction of phrases from unstructured text."
"While a text may have many applications, it has only one fundamental interpretation."
"Regular expressions help us define patterns that we can then find, test if they exist, and extract them."
"Named entity recognition is a task of recognizing all the mentioned entities in the text."
"For the new critics, a text is like a living organism."
"A text without context is a pretext for a proof text."
"Biblical studies focuses more directly on the text, its historical provenance, its grammatical meaning."
"Every number, every detail, even the structures underneath the text, evidence incredible craftsmanship."
"Read backwards... you're focusing more on the text and not the ideas."
"Semantic similarity is trying to assess how similar in meaning two pieces of text are."
"Natural language processing is all about uncovering some meaning from text."
"Paste in your text below and we'll extract the keywords for you."
"Everyone is applying principles of reason and logic and cause and effect to the text in order to understand what it really means."
"Meaning is never just one thing; text never just means one thing."
"Every number, every place name, even the linguistic structure of the text bears evidence of integrated design."
"Tidy text package lets us take text data and pull it apart."
"The Naive Bayes Algorithm is a generative learning algorithm in which given a piece of email, or Twitter message or some piece of text, we take a dictionary and put in zeros and ones depending on whether different words appear in a particular email."
"Count vectorizer is a great tool for this."
"Coherence in contrast relates to the macro level features of a text, which help it to make sense as a whole."
"Tokenization is a process of splitting the text into meaningful segments."
"...the real basis of literary criticism is the literary text itself, constituted simply of the medium of language, of words on the page."
"Sentiment analysis is a process of determining whether the text is positive, negative, or neutral."
"Taking review text like this is pretty interesting; we can do some cool stuff with text analysis."
"If your interpretation of a text doesn't take you to the text's own conclusion, you've probably missed the meaning of the text."
"Chroma is a very popular option in both Lang chain and Llama index, which combine to help you create a large corpus of text, turning them into some numerical representation that encapsulate a certain semantic meaning."
"Extractive question answering is where the answer can be extracted directly from the document itself."
"Use relevant details from Text C and develop the ideas presented in the text."
"The intelligence that this task is trying to get at is just can you read a text and understand it."
"You actually have to read it as a text that points beyond itself."
"It is certainly the case that judges take different approaches to interpreting the text."
"We're able to show that it's not just doing pattern matching and text recognition but is identifying the phrases based on the context in which they appear."
"Speech synthesis consists of text analysis and speech synthesis; both are important to achieve high-quality text-to-speech synthesis."
"What this dense layer is going to attempt to do essentially is look for patterns of words and try to classify them into either a positive review or a negative review."
"You could even use it as a discussion tool and talk about how breaking the text in different places might affect the way that the text is interpreted by the reader."
"Determine whether or not the text must be read more closely for a deeper understanding."
"As a part of the reading, you need to point out the right points: writer's purpose, tone, attitude, and the clear understanding of the information."
"Co-reference resolution is a really key task. It's used in all sorts of places."
"There's very little work on combining text and knowledge bases to do overall complex question answering that requires reasoning."
"These probabilistic topic models provide useful descriptive statistics for analyzing and understanding the latent structure of large text collections."
"Good readers also read to understand what the text says, how the text says it, and to understand what the text means."
"It's important to start with the first statement because we will more than likely find the answer in the beginning of the text."
"If you're interested in doing sentiment analysis on a bunch of text, you can use the data in your own inbox."
"Latent Semantic Analysis... allows us to extract relationships between documents and terms."
"It forms the basis of text analysis operations."
"Every string of text is indexed in VBA, so every character has a position."
"With a little work in text analysis here, we can get pretty close."
"The text is powerful and instead of debating the authorship, let's dive into the text."
"We saw how we could easily go through and identify the significant entities in this sample paragraph from chapter one of Harry Potter book one."