Категории

Encoding multi-layered Vega-Lite COVID-19 Geodata visualizations

Опубликовано: 08 Октябрь 2024
на канале: Databricks
2,004
25

Visualizations are a powerful tool for communicating results to end-users and stakeholders. Their development and life-cycle management are no less challenging than the underlying processes producing the results they communicate. Our team overcomes these challenges by leveraging Vega-Lite to encode visualizations as JSON objects and using the MLflow model registry as a visualization registry. During this presentation, we will walk through the process of creating a multi-layered Vega-Lite visualization using COVID-19 and Geodata, then managing it with the MLFlow model registry.

GitHub Repo: https://github.com/baumanab/mlflow_vi...

Demo: https://hub.gke.mybinder.org/user/bau... Databricks is proud to announce that Gartner has named us a Leader in both the 2021 Magic Quadrant for Cloud Database Management Systems and the 2021 Magic Quadrant for Data Science and Machine Learning Platforms. Download the reports here. https://databricks.com/databricks-nam...

play_arrow
3,006
23

Periscope gorgeous girl live

Periscope gorgeous girl live

play_arrow
10,566
201

Лев Барашков Соловьиная роща

Лев Барашков Соловьиная роща
play_arrow
304
18

I am not dead yet

I am not dead yet
play_arrow
11
0

Как найти золотые короля в Chicken Gun

Как найти золотые короля в Chicken Gun
play_arrow
13,248
414

If indian suv is a school 🔥🔥🔥

If indian suv is a school 🔥🔥🔥
play_arrow
4,650
137

Стихотворение '' Можно, я прийду к тебе во сне? '' Автор Михаил Шитов.

Стихотворение '' Можно, я прийду к тебе во сне? '' Автор Михаил Шитов.
play_arrow
1,401
41

НИКОГДА ТАК НЕ ДЕЛАЙТЕ!!!

НИКОГДА ТАК НЕ ДЕЛАЙТЕ!!!
play_arrow
29,585
609

Udise plus Student Data kaise bhare 2022-23 | udise sdms kaise bharen | SDMS | udise plus sdms |

Udise plus Student Data kaise bhare 2022-23 | udise sdms kaise bharen | SDMS | udise plus sdms |
Похожие видео
play_arrow
Mosaic AI Gateway - Secure and Govern your AI

Mosaic AI Gateway - Secure and Govern your AI
play_arrow
Data + AI Summit 2023

Data + AI Summit 2023
play_arrow
LLM Module 6: LLMOps | 6.7 Notebook Demo

LLM Module 6: LLMOps | 6.7 Notebook Demo
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.13.1 Notebook Demo Part 1

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.13.1 Notebook Demo Part 1
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.10 Task specific Evaluations

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.10 Task specific Evaluations
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.6 Fine Tuning: LLMs as a Service

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.6 Fine Tuning: LLMs as a Service
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.3 Applying Foundation LLMs

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.3 Applying Foundation LLMs
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.4 Fine Tuning: Few-shot Learning

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.4 Fine Tuning: Few-shot Learning
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.2 Module Overview

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.2 Module Overview
play_arrow
LLM Module 4: Fine-tuning and Evaluating LLMs | 4.1 Introduction

LLM Module 4: Fine-tuning and Evaluating LLMs | 4.1 Introduction
play_arrow
LLM Module 3 - Multi-stage Reasoning | 3.7.1 Notebook Demo Part 1

LLM Module 3 - Multi-stage Reasoning | 3.7.1 Notebook Demo Part 1
play_arrow
LLM Module 3 - Multi-stage Reasoning | 3.3 Prompt Engineering

LLM Module 3 - Multi-stage Reasoning | 3.3 Prompt Engineering
play_arrow
LLM Module 3 - Multi-stage Reasoning | 3.1 Introduction

LLM Module 3 - Multi-stage Reasoning | 3.1 Introduction
play_arrow
LLM Module 3 - Multi-stage Reasoning | 3.2 Module Overview

LLM Module 3 - Multi-stage Reasoning | 3.2 Module Overview
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.2 Notebook Demo Part 2

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.2 Notebook Demo Part 2
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.1 Notebook Demo Part 1

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.8.1 Notebook Demo Part 1
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.6 Best Practices

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.6 Best Practices
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.5 Vector Stores

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.5 Vector Stores
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.2 Module Overview

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.2 Module Overview
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.4 Filtering

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.4 Filtering
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.3 How does Vector Search work

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.3 How does Vector Search work
play_arrow
LLM Module 2 - Embeddings, Vector Databases, and Search | 2.1 Introduction

LLM Module 2 - Embeddings, Vector Databases, and Search | 2.1 Introduction
play_arrow
LLM Module 1 - Applications with LLMs | 1.8 Summary

LLM Module 1 - Applications with LLMs | 1.8 Summary
play_arrow
LLM Module 1 - Applications with LLMs | 1.9 Notebook Demo

LLM Module 1 - Applications with LLMs | 1.9 Notebook Demo