Все публикации

0:01:36

6 Ways to Optimize Power BI Dashboards for Speedy Performance

0:00:51

Data + AI Summit 2023

0:27:41

LLM Module 6: LLMOps | 6.7 Notebook Demo

0:15:18

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.13.1 Notebook Demo Part 1

0:02:58

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.10 Task specific Evaluations

0:02:56

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.6 Fine Tuning: LLMs as a Service

0:01:31

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.3 Applying Foundation LLMs

0:03:41

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.2 Module Overview

0:02:25

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.1 Introduction

0:16:43

LLM Module 3 - Multi-stage Reasoning | 3.7.1 Notebook Demo Part 1

0:07:44

LLM Module 3 - Multi-stage Reasoning | 3.7.2 Notebook Demo Part 2

0:02:51

LLM Module 3 - Multi-stage Reasoning | 3.1 Introduction

0:04:33

LLM Module 3 - Multi-stage Reasoning | 3.2 Module Overview

0:08:19

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.10 Notebook Demo Weaviate (Optional)

0:11:24

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.2 Notebook Demo Part 2

0:16:10

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.1 Notebook Demo Part 1

0:08:01

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.6 Best Practices

0:08:23

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.2 Module Overview

0:04:01

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.4 Filtering

0:06:35

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.3 How does Vector Search work

0:03:13

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.1 Introduction

0:23:49

LLM Module 1 - Applications with LLMs | 1.9 Notebook Demo

0:03:13

LLM Module 1 - Applications with LLMs | 1.6 Prompts

0:05:46

LLM Module 1 - Applications with LLMs | 1.7 Prompt Engineering