Published in Google Cloud - Community·Mar 1Member-onlyUpgrade Google Vertex AI Workbench Notebook Python VersionGoogle’s Vertex AI Notebooks are currently running on Python 3.7. You might need a more recent Python version to use newer Python features. — Fortunately, we can install a newer version in addition to the existing Python version using Conda. This way you can choose both kernels in the Vertex AI Workbench Notebook UI. Open a terminal in the notebook and create a new conda environment with the Python version you need.Google Cloud Platform1 min readGoogle Cloud Platform1 min read
Published in Google Cloud - Community·Feb 24Member-onlyReal Time Deep Learning Vector Similarity SearchA production scale vector similarity search with only 100 lines of code — Implementing the infrastructure to dynamically update and query a similarity index like Facebook’s Faiss or Spotify’s Annoy is a huge implementation effort. With the architecture in this article, we get it into production in minutes. If you haven't worked in that topic space before, I can recommend checking out my…Machine Learning5 min readMachine Learning5 min read
Published in Google Cloud - Community·Jan 29Member-onlyGoogle Vertex AI Batch PredictionsBatch predictions allow you to predict large amounts of data in parallel. — Vertex AI Batch Prediction is made for large datasets that would take too much time with an online prediction approach. It provides a scalable, serverless, and efficient service for cases where you don’t need an immediate response (asynchronous). Jump to the Notebook and Code All the code for this article is ready to use in a…Machine Learning7 min readMachine Learning7 min read
Published in Google Cloud - Community·Jan 29Member-onlyAdd Cloud Logging to your Vertex AI Batch Prediction JobsA simple way to circumvent the limited debugging and logging capabilities. — Vertex AI Batch Prediction jobs do not log errors to Cloud Logging. This is mainly due to the batch job running in a Google-managed project. This can be a big issue if something is not working as expected. Without logging, we are running nearly blind. Batch Predictions in production are…Machine Learning4 min readMachine Learning4 min read
Published in Google Cloud - Community·Nov 22, 2022Member-onlyHow to use previously created artifacts with Vertex AI PipelinesGoogle provides a bunch of pre-built components for Vertex AI Pipelines. Those components produce artifacts as output and use them as input for other pre-built components. As long as those artifacts are produced and consumed within the same pipeline, we can easily use them (In that case, there is no…Google Cloud Platform5 min readGoogle Cloud Platform5 min read
Published in Google Cloud - Community·Nov 18, 2022Member-onlyML Experiment Tracking with Vertex AIExperimenting with machine learning models can get messy — We need to be organized and have a process to keep track of all the different architectures and parameters we set when experimenting and training our models. Vertex AI Experiments helps you easily track, compare and search within your experiments. There are many products on the market, and Vertex AI…Machine Learning7 min readMachine Learning7 min read
Published in Google Cloud - Community·Sep 23, 2022Member-onlyGoogle Vertex AI Model Registry and VersioningGoogle released support for versioning models earlier this year. However, the official documentation on how to use it is still very limited. This article should help you shed light on the Vertex AI SDK and how to use it to version your models. Until recently, most of us were confronted…Vertex AI4 min readVertex AI4 min read
Published in Google Cloud - Community·Sep 16, 2022Member-onlyRecommendation Systems with Deep LearningA practical approach using Google Cloud — Matrix multiplications are still widely used for Recommendation Systems. And they are a great starting point if you want to build a quick and easy solution to deliver great recommendations to your customers. Nothing wrong with that. Keep it simple until you make it complicated. In this article, we want…Recommendation System10 min readRecommendation System10 min read
Published in Google Cloud - Community·Aug 15, 2022Member-onlyServing Machine Learning models with Google Vertex AIDeploying and serving any kind of machine learning model at any scale. — Companies frequently deploy their models to virtual machines (Google Compute Engine or even on-prem machines). This is something that should be avoided. Google Cloud provides a dedicated service called Vertex AI Endpoints to deploy your models. Vertex AI Endpoint provides great flexibility compared with easy usage. You can keep it…Machine Learning10 min readMachine Learning10 min read
Published in Google Cloud - Community·Jul 6, 2022Member-onlyRecommendation Systems with BigQuery ML and Vertex AI Pipelines using Matrix FactorizationHow to build a fully automated recommendations pipeline in under 45 minutes — Matrix factorizations are widely used for Recommendation Systems. They are a great and easy starting point if you want to build a quick and easy solution to deliver great recommendations to your customers. This article covers the steps needed to automate a BigQueryML Matrix Factorization recommendation pipeline. Including automatic handling…Recommendations System5 min readRecommendations System5 min read
