Labs and demos for courses for GCP Training (http://cloud.google.com/training).
Role in this project:
Data Scientist Contributions:26 commits, 15 PRs, 5 pushes in 5 years 4 months
Contributions summary:Ajay's contributions focused on enhancing machine learning training pipelines within the Google Cloud Platform environment. They added and modified code in `feateng.ipynb` to include a `REPO` variable, which is used to specify the project's directory. The user also incorporated the `REPO` variable into the training and prediction commands using `gcloud ml-engine`. Furthermore, the user worked on a `train_deploy.ipynb` notebook.
gcpgoogle-cloud-platformgoogle-cloudtraining
Role in this project:
MLOps Engineer Contributions:43 commits, 42 PRs, 61 pushes in 3 months
Contributions summary:Ajay primarily focused on updating and modifying various Jupyter notebooks related to TFX pipelines and KFP (Kubeflow Pipelines) within the Google Cloud Platform MLOps framework. Their changes involve adjusting pipeline configurations, specifically modifying parameter settings, installation instructions, and command definitions within pipeline YAML files. The user's contributions are centered around adapting and troubleshooting existing workshop materials to ensure their proper execution within the GCP environment. This includes addressing known issues, updating package installation instructions, and fixing bugs to improve workflow.