James Briggs Courses

Llama Index 101 with Vector DBs and GPT 3.5

Explore Llama-index with Pinecone vector database for semantic search and LLM retrieval augmentation. Learn about Documents, Nodes, vectorstore objects, and making queries in this practical tutorial.

• YouTube
• 19 minutes
• On-Demand
• Free Video

Open LLaMa in LangChain and Hugging Face

Learn to implement Open-LLaMa in Hugging Face and LangChain, covering tokenization, stopping criteria, pipeline setup, and chatbot creation. Gain practical skills in open-source AI development.

• YouTube
• 23 minutes
• On-Demand
• Free Video

Nvidia's NeMo Guardrails - Full Walkthrough for Chatbots - AI

Comprehensive walkthrough of Nvidia's NeMo Guardrails library for building safer, more controlled chatbots and AI assistants. Covers implementation, dialogue flows, and practical Python examples.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Llama 2 in LangChain - First Open Source Conversational Agent

Explore Llama 2, the top open-source LLM, in LangChain. Learn to implement a 70B parameter chat model using Hugging Face and create a conversational agent with practical examples.

• YouTube
• 27 minutes
• On-Demand
• Free Video

Chatbot with LangChain

Learn to create an open-source chatbot using MPT-30B, a powerful language model, with LangChain. Explore implementation, tokenization, and building a functional chatbot on a single GPU.

• YouTube
• 21 minutes
• On-Demand
• Free Video

Fixing LLM Hallucinations with Retrieval Augmentation in LangChain

Learn to enhance LLM accuracy using retrieval augmentation in LangChain. Explore data preprocessing, embedding creation, vector database setup, and generative question-answering with citations for improved AI responses.

• YouTube
• 31 minutes
• On-Demand
• Free Video

Create Custom Tools for Chatbots in LangChain

Learn to create custom tools for chatbots using LangChain, enhancing AI capabilities with web search, math, code execution, and image understanding. Explore practical examples and advanced agent techniques.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Chatbot with LangChain Agents + GPT 3.5

Learn to build a conversational agent using LangChain and GPT-3.5, leveraging vector search retrieval to provide context from Lex Fridman's podcast for intelligent responses.

• YouTube
• 33 minutes
• On-Demand
• Free Video

LangChain Agents Deep Dive with GPT 3.5 - LangChain

Explore LangChain agents to enhance LLMs with tools for logic, calculation, and search. Learn implementation, customization, and various agent types to superpower your AI applications.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Pinecone's New Hybrid Search - The Future of Search?

Explore Pinecone's hybrid search, combining vector and traditional methods for improved relevance and adaptability in semantic search and information retrieval.

• YouTube
• 20 minutes
• On-Demand
• Free Video

OpenAI's CLIP for Zero Shot Image Classification

Explore OpenAI's CLIP model for flexible computer vision classification without retraining, enabling generalization to new classes and images beyond initial training data.

• YouTube
• 22 minutes
• On-Demand
• Free Video

OpenAI CLIP Explained - Multi-modal ML

Explore OpenAI's CLIP model, bridging text and image understanding. Learn about multi-modal AI, CLIP's functionality, and its applications in encoding, classification, and object detection.

• YouTube
• 34 minutes
• On-Demand
• Free Video

Bag of Visual Words for Image Classification and Retrieval

Learn to build image embeddings using the Bag of Visual Words technique for image retrieval, object detection, and classification in computer vision applications.

• YouTube
• 56 minutes
• On-Demand
• Free Video

How to Build a Q&A Reader Model in Python - Open-Domain QA

Learn to build an open-domain question-answering system in Python, covering data preprocessing and model fine-tuning for efficient information retrieval from large datasets.

• YouTube
• 25 minutes
• On-Demand
• Free Video

Making the Most of Data - Augmented SBERT

Explore data augmentation in NLP, focusing on AugSBERT for low-resource domains. Learn techniques to generate and label data automatically, enhancing ML model performance without manual annotation.

• YouTube
• 55 minutes
• On-Demand
• Free Video