ML Articles Sascha Heyer

A comprehensive list of articles that provides you knowledge about Machine Learning on Google Cloud.

This website is for the sole purpose of keeping an overview of all ML-related articles I published on medium.com. Almost every article contains a notebook with code for you to use, including a YouTube video.

Generative AI

1. Generative AI — Getting Started with PaLM 2
2. Generative AI — The Evolution of Machine Learning Engineering
3. Generative AI — Best Practices for LLM Prompt Engineering
4. Generative AI — Document Retrieval and Question Answering with LLMs
5. Generative AI — Mastering the Language Model Parameters for Better Outputs

Recommendation Systems

1. Recommendation Systems with Deep Learning
2. Recommendation System with BigQuery ML and Vertex AI Pipelines using Matrix Factorization

Vector Search

1. Image Similarity with Deep Learning
2. All you need to know about Google Vertex AI Matching Engine
3. Real Time Deep Learning Vector Similarity Search

ML Ops / Pipelines

1. The Easiest Way to Run Google Vertex AI Pipelines
2. How to use previously created artifacts with Vertex AI Pipelines
3. ML Experiment Tracking with Vertex AI
4. Google Vertex AI Model Registry and Versioning
5. Vertex AI Pipelines vs. Cloud Composer for Orchestration
6. How to implement CI/CD for your Vertex AI Pipeline

Notebooks

1. Automatically Shut Down Vertex AI User-Managed Notebooks
2. Upgrade Google Vertex AI Workbench Notebook Python Version

Training / Serving / Prediction

1. Google Vertex AI Batch Predictions
2. Add Cloud Logging to your Vertex AI Batch Prediction Jobs
3. Serving Machine Learning models with Google Vertex AI
4. Train Machine Learning models with Vertex AI Training
5. AutoML just another tool in your toolbox

Cost Optimization

1. How to reduce your ML model inference costs on Google Cloud
2. Optimizing TensorFlow Training Time for Better Performance

Explainable AI

1. Explainable AI with Google Cloud Vertex AI

YouTube

Feel free to check out my YouTube channel, which provides additional information on the articles and the code.

https://www.youtube.com/@ml-engineer