This repo is a companion to my LinkedIn Learning course 'GCP ML Essentials' - at https://www.linkedin.com/learning/google-cloud-platform-for-machine-learning-essential-training
Google Cloud Platform Analytics and Machine Learning Samples for services shown below.
Samples currently include the following:
-
GCP Colabs (Jupyter-style) notebook
- for BigQuery (connect & run SQL queries)
- for BigQueryML (connect, build, train and predict using ML model) IMPORTANT: Use link in each notebook to open it in GCP Colabs environment
- for TensorFlow w/GPU - speed test
- for production workloads, you may want to pay for and use ColabPro ($10/mo) for faster GPU, longer notebook runtimes and more memory
-
Scripts and code samples
- for BigQueryML in SQL
- Vision API
- Natural Language API
- for AutoML Vision & Natural Language
- for Datalab (Jupyter-notebooks on GCE)
- for TensorFlow
- Docker image
- Virtual Machine image
- MLEngine
- TF Probability
- Cloud TPUs
- Resources
- Sample Data
- GCP public datasets - https://console.cloud.google.com/marketplace/browse?filter=solution-type:dataset
- TensorFlow Hub for Image, Text, Video (models + data) - https://tfhub.dev/
- TF Datasets - https://www.tensorflow.org/datasets/catalog/overview
- Google Dataset search - https://datasetsearch.research.google.com/
- Example Models
- GCP AI Hub - https://aihub.cloud.google.com/u/0/
- TensorFlow (Model) Hub - https://www.tensorflow.org/hub
- TensorFlow Model Garden - https://github.com/tensorflow/models/tree/master/official
- YouTube Adventures In The Cloud series - https://www.youtube.com/AdventuresInTheCloud
- Learning about APIs & Concepts
- Trying out DocumentAI - https://cloud.google.com/document-ai
- Teachable Machines (teach kids AI) - https://teachablemachine.withgoogle.com/
- End-to-end tutorial with ML tools - https://cloud.google.com/architecture/building-a-propensity-model-for-financial-services-on-gcp
- Aweseome TensorFlow (list of currated links) - https://github.com/jtoy/awesome-tensorflow
- Open source course on ML Foundations (homemade-machine-learning) - https://github.com/trekhleb/homemade-machine-learning
- DeepMind Educational Resources (notebooks on Github) - https://github.com/deepmind/educational
- AI Ethics/Tools
- TensorFlow Responsible API - https://www.tensorflow.org/responsible_ai
- TensorFlow Fairness Indicators - https://www.tensorflow.org/tfx/guide/fairness_indicators
- Article - addressing bias in COVID-19 data - https://cloud.google.com/blog/products/ai-machine-learning/google-and-harvard-improve-covid-19-forecasts
- Article - monitor models for drift - https://cloud.google.com/blog/topics/developers-practitioners/monitoring-feature-attributions-how-google-saved-one-largest-ml-services-trouble
- Sample Data
To setup general prerequisites see the SETUP.md
file in this Repo.