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alexioannides

Python source code for generating my personal website - hosted by GitHub pages at alexioannides.github.io - using the Pelican framework for static websites, together with Flex theme.

The output of the build process is written to the output folder in the root directory, that is not version controlled using this repository. Instead, the output directory has its own repository at alexioannides, that is necessary for hosting with GitHub pages.

Development Setup

The package's 3rd party dependencies are described in requirements.txt. Create a new virtual environment and install these dependencies as follows,

python3 -m venv .venv
source .venv/bin/activate
pip install -r requirements.txt

Building the Website

To build the website we need to call Pelican,

pelican

Testing the Site Locally

We recommend setting RELATIVE_URLS = True when testing (do not forget to revert this before deploying) and then executing the following,

pelican --listen output

A test version of the website will then be available at http://localhost:8000.

Deploying to GitHub Pages

After testing locally, first of all ensure that RELATIVE_URLS = False, rebuilding the website if necessary. Then, make sure that you are still in the output directory and remember that this is version controlled by a different repository, that now needs new changes to be committed and pushed to master as usual - e.g.,

git add -A
git commit -m "latest changes to alexioannides.github.io"
git push origin master

The updated website is usually available within a minute or two.

Alex Ioannides's Projects

aitoolz icon aitoolz

Various Python tools, by Alex Ioannides (AI). Some of them might be useful for artificial intelligence and some of them might not.

alexioannides icon alexioannides

Python source code for generating my website at alexaioannides.github.io.

bodywork-core icon bodywork-core

An open-source deployment automation tool for machine learning in Python, on Kubernetes. Run batch jobs, serve models and deploy ML pipelines without the DevOps headache. Accelerated MLOps 🚀

bodywork-mlops-demo icon bodywork-mlops-demo

Demonstrating how Bodywork can be used to deploy a simulation of the lifecycle of a train-and-serve ML pipeline, responding to new data undergoing concept drift.

kfp-component-lib icon kfp-component-lib

A pattern for developing libraries of reusable Kubeflow Pipeline components.

lime-interpretable-ml icon lime-interpretable-ml

An example of how the LIME algorithm can be used to provide real-world insight into the decision processes of a 'black-box' machine learning algorithm - in this case a Radom Forest regressor.

llm-toolz icon llm-toolz

Tools for experimenting and working with LLMs.

ml-workflow-automation icon ml-workflow-automation

Python Machine Learning (ML) project that demonstrates the archetypal ML workflow within a Jupyter notebook, with automated model deployment as a RESTful service on Kubernetes.

py-docker-aws-example-project icon py-docker-aws-example-project

Automated testing and deployment of a simple Flask-based (RESTful) micro-service to a production-like environment on AWS, using Docker containers and Travis-CI.

pycaret-mlops icon pycaret-mlops

Using PyCaret with Bodywork to deploy ML pipelines to Kuberentes

pymc-example-project icon pymc-example-project

Example PyMC3 project for performing Bayesian data analysis using a probabilistic programming approach to machine learning.

registerit icon registerit

Have an idea for a Python package? Register the name on PyPI 💡

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