scy6500 / nerf-workspace

NeRF Workspace

This branch is for creating Ainize Workspace images for NeRF_PL.

Installed Python libraries

Machine Learning Frameworks

• Tensorflow
• scikit-learn
• PyTorch
• Keras
• XGBoost
• LightGBM
• JAX
• Pytorch-lightning
• StatsModels
• LightGBM

Data Visualization

• Matplotlib
• Bokeh
• Plotly
• Seaborn
• Dash
• Altair
• Pandas Profiling
• HoloViews
• WordCloud
• missingno

Text Data & NLP

• spaCy
• nltk
• gensim
• snowballstemmer

Image Data

• Pillow
• scikit-image
• torchvision
• MoviePy
• imageio
• opencv-python
• Albumentations

Graph Data

• networkx

Geospatial Data

• geopy

Time Series Data

• Prophet

Data Containers & Dataframes

• pandas
• numpy
• h5py
• xarray
• Bottleneck
• numexpr

Data Pipelines & Streaming

• joblib

Distributed Machine Learning

• dask
• distributed

Hyperparameter Optimization & AutoML

• Hyperopt

Reinforcement Learning

• Dopamine

Workflow & Experiment Tracking

• Tensorboard

Model Interpretability

• arviz
• yellowbrick

Probabilistics & Statistics

• PyMC3
• tensorflow-probability
• patsy

Sklearn Utilities

• imbalanced-learn

How to Test Your Image

Build Docker Image

docker build -t <image-name> .

Run Docker

docker run -d -p 8000:8000 -p 8010:8010 -p 8020:8020 <image-name>

Run Docker with Password

docker run -d -p 8000:8000 -p 8010:8010 -p 8020:8020 -e PASSWORD=<password> <image-name>

Run Docker with Github Repo

docker run -d -p 8000:8000 -p 8010:8010 -p 8020:8020 -e GH_REPO=<github-repo> <image-name>

Run Docker with password and Github Repo

docker run -d -p 8000:8000 -p 8010:8010 -p 8020:8020 -e PASSWORD=<password> -e GH_REPO=<github-repo> <image-name>

• Jupyter Notebook : http://server-address:8000/

• Visual Studio Code : http://server-address:8010/

• Terminal - ttyd : http://server-address:8020/

• You can download this image from Docker Hub.

How to use this image in Ainize Workspace

1. Click the "Create your workspace" button on the Ainize Workspace page.
2. As the Container option, select "Import from github".
3. Click the "Start with repo url" button.
4. Put "https://github.com/ainize-workspace-collections/ml-workspace" in "Enter a Github repo url". And select this branch.
5. Select the required tool(s) and click the OK button.
6. Click "Start my work" after selecting the machine type. Now, enjoy your own Ainize Workspace! 🎉