Oreilly - Quick Start Guide to Large Language Models (LLMs) ChatGPT, Llama, Embeddings, Fine-Tuning, and Multimodal AI, 2nd Edition 2024-8

4.3 GB | 00:37:38 | mp4 | 1280X720 | 16:9
Genre:eLearning |Language:English

Files Included :
1 1 What Are Large Language Models (120.87 MB)
1 2 Popular Modern LLMs (97.86 MB)
1 3 Applications of LLMs (16.26 MB)
10 1 BERT for Multi-label Classification Part 1 (55.19 MB)
10 2 BERT for Multi-label Classification Part 2 (125.25 MB)
10 3 Writing LaTeX with GPT-2 (89.99 MB)
10 4 Case Study Sinan s Attempt at Wise Yet Engaging Responses Sawyer (100.07 MB)
10 5 Instruction Alignment of LLMs Supervised Fine-Tuning (172.22 MB)
10 6 Instruction Alignment of LLMs Reward Modeling (143.83 MB)
10 7 Instruction Alignment of LLMs RLHF (164.15 MB)
10 8 Instruction Alignment of LLMs Using Our Instruction-Aligned LLM (118.99 MB)
11 1 Cost Projecting and Deploying LLMs to Production (39.86 MB)
11 2 Knowledge Distillation (107.93 MB)
12 1 Evaluating Generative Tasks Part 1 (71.52 MB)
12 2 Evaluating Generative Tasks Part 2 (107.56 MB)
12 3 Evaluating Understanding Tasks (100.8 MB)
12 4 Probing LLMs for world model (48.76 MB)
2 1 Introduction to Semantic Search (64.18 MB)
2 2 Building a Semantic Search System (148.61 MB)
2 3 Optimizing Semantic Search with Cross-Encoders and Fine-Tuning (160.95 MB)
3 1 Introduction to Prompt Engineering (121.85 MB)
3 2 Working with Prompts Across Models (22.42 MB)
3 3 Building a Retrieval-Augmented Generation BOT with ChatGPT and GPT-4 (170.8 MB)
4 1 Introduction to Retrival Augmented Generation (RAG) (54.13 MB)
4 2 Building a RAG bot (113.33 MB)
4 3 Using Open Source Models with RAG (103.61 MB)
4 4 Expanding into AI Agents (116.64 MB)
5 1 Transfer Learning A Primer (26.17 MB)
5 2 The OpenAI Fine-Tuning API (29.78 MB)
5 3 Case Study Predicting with Android App Reviews Part 1 (37.35 MB)
5 4 Case Study Predicting with Android App Reviews Part 2 (224.34 MB)
6 1 InputOutput Validation (46.03 MB)
6 2 Batch Prompting + Prompt Chaining (40.08 MB)
6 3 Chain-of-Thought Prompting (60.08 MB)
6 4 Preventing Prompt Injection Attacks (21.51 MB)
6 5 Assessing an LLM s Encoded Knowledge Level (27.96 MB)
7 1 Case Study Building an Anime Recommendation System (53.87 MB)
7 2 Using OpenAI s Embedded Models (120.55 MB)
7 3 Fine-tuning an Embedding Model to Capture User Behavior (152.09 MB)
8 1 Introduction to AI Alignment (72.04 MB)
8 2 Evaluating Alignment Plus Ethics (91.52 MB)
9 1 The Vision Transformer (13.29 MB)
9 2 Using Cross Attention to Mix Data Modalities (17.72 MB)
9 3 Case Study Visual QA Setting Up Our Model (112.92 MB)
9 4 Case Study Visual QA Setting Up Our Parameters and Data (105.41 MB)
9 5 Introduction to Reinforcement Learning from Feedback (58.54 MB)
9 6 Aligning FLAN-T5 with Reinforcement Learning from Feedback (130.07 MB)
Module 3 Advanced LLM Usage (27.49 MB)
Module Introduction (1) (19.68 MB)
Module Introduction (21.98 MB)
Quick Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs) Introduction (1) (22.54 MB)
Quick Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs) Introduction (22.54 MB)
Quick Guide to ChatGPT, Embeddings, and Other Large Language Models (LLMs) Summary (27.04 MB)
Topics (1) (4.3 MB)
Topics (10) (4.03 MB)
Topics (11) (4.19 MB)
Topics (2) (5.29 MB)
Topics (3) (4.63 MB)
Topics (4) (5.17 MB)
Topics (5) (3.3 MB)
Topics (6) (4.96 MB)
Topics (7) (5.56 MB)
Topics (8) (5.68 MB)
Topics (9) (5.76 MB)
Topics (5.98 MB)
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