https://github.com/basedrhys/i2k-tutorial
Tutorial Assets and Guides for the 2020 I2K WekaDeeplearning4j tutorial
https://github.com/basedrhys/i2k-tutorial
Last synced: 4 months ago
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Tutorial Assets and Guides for the 2020 I2K WekaDeeplearning4j tutorial
- Host: GitHub
- URL: https://github.com/basedrhys/i2k-tutorial
- Owner: basedrhys
- Created: 2020-11-20T07:24:04.000Z (over 5 years ago)
- Default Branch: master
- Last Pushed: 2020-12-08T01:47:53.000Z (over 5 years ago)
- Last Synced: 2025-10-04T09:47:48.807Z (9 months ago)
- Size: 3.85 MB
- Stars: 2
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# I2K 2020 - WekaDeeplearning4j Tutorial
Welcome to the **WekaDeeplearning4j** tutorial for I2K (Images to Knowledge) 2020! This repo contains the tutorial docs which showcase a number of features within **WekaDeeplearning4j** for image analysis and classification.
## Asset Pack
Before you get started, check out the [asset pack download page](./0-asset_pack.md) for instructions on downloading the tutorial asset pack. This contains datasets and models you'll need for this tutorial.
[Google Slides Link](https://docs.google.com/presentation/d/1IXKmsZV1366NVCAV-ev6ZESO_BYPD0dM_T6yoc_J2hU/edit?usp=sharing)
## Table of Contents
It is recommended to view these tutorials on the [Github Pages site](https://basedrhys.github.io/I2K-Tutorial/).
1. [Introduction & Setup](./1-introduction_setup.md)
2. [**Training** with the `Dl4jMlpClassifier`](./2-training.md)
3. [CNN **Feature Extraction** with the `Dl4jMlpFilter`](./3-feature_extraction.md)
4. [**Model Inference** with the `Dl4jCNNExplorer`](./4-inference.md)
## Contact Me
If you have any feedback on the tutorial/WekaDeeplearning4j, or just want to chat, feel free to get in touch with me via [Github](https://github.com/basedrhys), [LinkedIn](https://www.linkedin.com/in/rhyscompton-nz/), [Twitter](https://twitter.com/rhyscompton_nz), or Email (`rhys.compton@gmail.com`)