Repolode
Submit
GoogleCloudPlatform

GoogleCloudPlatform/asl-ml-immersion

Google Cloud Advanced Solutions Lab course materials: notebooks, labs and code samples for ML and generative AI on Google Cloud.

View on GitHub
Stars
2,616
Forks
1,539
Open issues
20
Last commit
14 hours ago

What is it?

This repository collects hands-on training material for machine learning and generative AI on Google Cloud, maintained by Google Cloud's Advanced Solutions Lab team. It is organized into three modules: asl_core covers model architectures such as DNNs, CNNs, RNNs, transformers and SNGP across tabular, image, text and time-series data, mostly in TensorFlow and Keras. asl_mlops covers operationalizing TensorFlow, scikit-learn and PyTorch models with training, tuning, serving and Kubeflow pipelines. asl_genai covers Gemini-based generative AI and agent systems built with frameworks like Google ADK.

Each topic folder contains a labs directory with notebooks that have TODOs to fill in, and a solutions directory to check your work against. Setup is done through a script run in Cloud Shell, followed by a make command inside the target environment to build virtual environments and Jupyter kernels. Environments are tested on Vertex AI Workbench and Cloud Workstations, and a GPU is optional for most notebooks. Using the labs incurs Google Cloud charges.

Key features

  • 01Covers DNN, CNN, RNN, transformer and SNGP models across tabular, image, text and time-series data.
  • 02Provides MLOps notebooks for training, tuning and serving TensorFlow, scikit-learn and PyTorch models on Google Cloud.
  • 03Includes generative AI and agent notebooks using Gemini and Google ADK.
  • 04Each topic has labs with TODOs and solutions for self-checking.
  • 05Includes a setup script that configures APIs, IAM and storage buckets.

Use cases

  • Working through a structured bootcamp on ML on Google Cloud.
  • Learning how to deploy TensorFlow or PyTorch models with Kubeflow pipelines.
  • Building a first Gemini-based agent with Google ADK using the provided samples.

Quick start

  1. 1

    Clone the repository

    git clone --depth 1 https://github.com/GoogleCloudPlatform/asl-ml-immersion.git
  2. 2

    Run the setup script in Cloud Shell from inside the cloned folder

    bash scripts/setup_env.sh
  3. 3

    Build the environment (venvs and Jupyter kernels) from inside your Google Cloud environment

    make

Things to know

  • Designed to run on Google Cloud, and using its products incurs charges.
  • Not an officially supported Google product.
  • Only Googlers can currently contribute to the repository.

In collections

Open-source AI agent frameworks & apps

Topics

#machine-learning#generative-ai#tensorflow#google-cloud#notebooks#mlops#agents#tutorial#adk#adk-pyth

FAQ

What is asl-ml-immersion?
Google Cloud Advanced Solutions Lab course materials: notebooks, labs and code samples for ML and generative AI on Google Cloud. This repository collects hands-on training material for machine learning and generative AI on Google Cloud, maintained by Google Cloud's Advanced Solutions Lab team. It is organized into three modules: asl_core covers model architectures such as DNNs, CNNs, RNNs, transformers and SNGP across tabular, image, text and time-series data, mostly in TensorFlow and Keras. asl_mlops covers operationalizing TensorFlow, scikit-learn and PyTorch models with training, tuning, serving and Kubeflow pipelines. asl_genai covers Gemini-based generative AI and agent systems built with frameworks like Google ADK.
Is asl-ml-immersion free to use? What license does it have?
asl-ml-immersion is open source under the Apache-2.0 license. Check the license terms before using it in commercial products.
Is asl-ml-immersion still maintained?
Actively maintained. The last commit to asl-ml-immersion was on Nov 6, 2026.
What can I use asl-ml-immersion for?
Working through a structured bootcamp on ML on Google Cloud. Learning how to deploy TensorFlow or PyTorch models with Kubeflow pipelines. Building a first Gemini-based agent with Google ADK using the provided samples.
How do I install asl-ml-immersion?
Clone the repository: git clone --depth 1 https://github.com/GoogleCloudPlatform/asl-ml-immersion.git Run the setup script in Cloud Shell from inside the cloned folder: bash scripts/setup_env.sh Build the environment (venvs and Jupyter kernels) from inside your Google Cloud environment: make
Where can I get asl-ml-immersion?
The source code and installation instructions are on GitHub: https://github.com/GoogleCloudPlatform/asl-ml-immersion

Summary generated by AI from the project's README. GitHub stats refresh daily.

Related projects