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This course covers building prompt systems with OpenAI GPT-3, few-shot training, adding external info and final thoughts on generative AI and prompts.
This course covers 4 components of LangChain and uses Hugging Face and OpenAI LLMs to build and analyze models. Students get to experience GPT-3 and see the final results.
Learn to build a generative AI for question-answering using Python in less than an hour with James Briggs. Understand AI, data preprocessing, text embedding, and get results.
Learn to use Falcon 40B, the top-performing open-source Large Language Model, with Hugging Face Transformers and LangChain to create chatbots. Offered by James Briggs.
Learn to interact with the web using Python, covering essentials like APIs, JSON, and Python requests. Offered by James Briggs, it takes less than an hour.
for chatbots. Learn about implementing memory for better conversational AI, explore LangChain's Memory & see examples.
Learn to apply fast and accurate filters to vector searches on massive datasets with James Briggs' under 1-hour material, including Pinecone's solution to filtering.
Learn the traditional approach to Locality Sensitive Hashing (LSH) with James Briggs. This under 1-hour material covers shingling, MinHashing, and banded LSH function.
Learn to train and test an Italian BERT model from scratch with James Briggs. This under 1-hour tutorial covers DataLoader, RoBERTa config, training loop, and testing.
Learn to implement Convolutional Neural Networks (CNNs) for computer vision tasks using Python and PyTorch in under an hour with James Briggs.
Learn to apply sentiment analysis to large datasets using NLP transformers and Pinecone, with a focus on the hotel industry, in under an hour with James Briggs.
Explore the merger of vision and language in machine learning with Vision Transformers (ViT). Learn to implement ViT using Python and Hugging Face for image classification in under an hour.
Learn to implement zero-shot object detection using OpenAI's CLIP in under an hour with James Briggs. No model fine-tuning or data annotation required.
Learn to enhance YouTube search using OpenAI's Whisper, transformers, and vector search in this short, project-based offering by James Briggs.
Learn to fine-tune classification models using vector search with less than 100 labeled examples in under an hour with James Briggs.
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