To showcase 100 Wave applications on various data science and machine learning workstreams for beginners, intermediates as well as experts.
H2O Wave is a product for building browser-based, realtime and interactive applications entirely using Python.
It empowers Data Scientists to quickly spin up beautiful dashboards as well as full-fledged web applications for demonstrating data science workflows.
There are a total of 100 Wave applications broadly divided into 10 sets, with 10 applications each. It is subject to periodic updates and changes.
✅ Structured as templates & tutorials - Choose your style
✅ Suitable for beginners, intermediates & experts - Choose your level
It is recommended to go through the sets in order for best experience, but you may explore them in any order depending on your expertise.
Set 01 • Skeleton Apps
| App | Level | Title | Description |
|---|---|---|---|
| 1 | Beginner | Hello Wave | Hello World example |
| 2 | Beginner | Basic Template | Building blocks to kickstart an app |
| 3 | Beginner | Theme Switch | Switch between light and dark modes |
| 4 | Beginner | CSV Loader | Load a csv file into a table |
Set 02 • Data Apps
| App | Level | Title | Description |
|---|---|---|---|
| 1 | Beginner | Datatable Playground | Explore Python Datatable with tabular datasets |
| 2 | Intermediate | NER Annotation | Annotate entities for Named-Entity Recognition tasks |
| 3 | Intermediate | Image Annotation | Annotate images for computer vision tasks |
Set 08 • Deep Learning Apps
| App | Level | Title | Description |
|---|---|---|---|
| 1 | Expert | Automatic Speech Recognition | Speech to text in English using Wav2Vec model |
| 2 | Expert | Whisper | Speech to text using OpenAI's Whisper model |
Set 10 • GPU Apps
| App | Level | Title | Description |
|---|---|---|---|
| 1 | Intermediate | Stable Diffusion | Generate images from prompts using Stable Diffusion model |
P.S. Every application can be run independently
Please create an Issue for any improvements, suggestions or errors in the content.
You can also tag @vopani on Twitter for any other queries or feedback.
This project is licensed under the Apache License 2.0.