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OasisLMS
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AI 101 - Class Recordings
Recording Class 7
Recording Class 7
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Video Transcription
Video Summary
The session focused on reviewing homework, explaining statistical concepts like mean and standard deviation, and exploring topics in machine learning and natural language processing (NLP). Initially, the instructor explained how to calculate the mean and standard deviation for different data sets and clarified when to use different formulas for populations versus samples. The session then covered concepts related to NLP and machine learning, emphasizing the use of embeddings and large language models (LLMs) like ChatGPT. Embeddings convert words into numerical vectors, which the models use to understand semantic relationships. Cosine similarity, a metric for comparing vector similarity, was explained. Retrieval Augmented Generation (RAG) was introduced as a method combining document retrieval with generation to ensure responses are contextually relevant and accurate. The session included a demonstration of the Pix2Pix model, an image-to-image translation tool. Various aspects of embeddings, including their use in Word2Vec and the differences with LLM embeddings, were discussed. The instructor answered questions about NLP applications, AI chatbots, and the technical details behind RAG and embeddings, stressing their importance in improving AI interactions.
Keywords
mean
standard deviation
machine learning
natural language processing
embeddings
large language models
cosine similarity
retrieval augmented generation
Pix2Pix model
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