Discover @AlexIoannides Open Source projects

Alex Ioannides (@AlexIoannides)

AlexIoannides

Stars
1,968
Global Rank 15,565 (Top 0.6 %)
Followers 382
Following 11
Registered almost 11 years ago
Most used languages

Jupyter Notebook
43.8 %

Python
31.3 %

R
12.5 %

CSS
6.3 %

HTML
6.3 %
Location 🇬🇧 United Kingdom
Country Total Rank 762
Country Ranking

R
79

Jupyter Notebook
109

Python
127

CSS
1,770

HTML
4,803

pyspark-example-project

Example project implementing best practices for PySpark ETL jobs and applications.

kubernetes-mlops

MLOps tutorial using Python, Docker and Kubernetes.

pymc-example-project

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

Jupyter Notebook

py-package-template

Python package template project for kick-starting new Python projects.

pipeliner

Machine learning pipelines for R.

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.

Jupyter Notebook

elasticsearchr

Lightweight Elasticsearch client for R.

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.

pymc-stochastic-process

Demonstrating the benefits of using Bayesian Inference and PYMC3 for estimating the parameters of stochastic processes commonly used in quantitative finance.

Jupyter Notebook

pymc-advi-hmc-demo

Demonstrating HMC and ADVI algorithms for Bayesian data analysis using PYMC3.

Jupyter Notebook

data-science-and-ml-notebook

Data science and ML engineering notebooks and demos

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.

Jupyter Notebook

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.

Jupyter Notebook

pycaret-mlops

Using PyCaret with Bodywork to deploy ML pipelines to Kuberentes

Jupyter Notebook

alexioannides

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

alexioannides.github.io

My GitHub Pages website and blog about all things (data) science and probably a lot more.

registerit

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