InTowards Data SciencebyAkila SomasundaramTensorFlow Transform: Ensuring Seamless Data Preparation in ProductionLeveraging TensorFlow Transform for scaling data pipelines for production environmentsJul 8
Manjinder SinghEnsuring Model Reliability in the Real World: A Guide to TensorFlow Data Validation (TFDV)Building a machine-learning solution in a Jupyter Notebook is one thing, but deploying it in the real world is another. In real-time…Dec 27, 20231
InTowards Data SciencebyAkila SomasundaramValidating Data in a Production Pipeline: The TFX WayA deep dive into data validation using Tensorflow Data ValidationJun 22Jun 22
InThe Deep HubbyEva RevearMLOps with KaggleX: Deploying a Recommendation System with Tensorflow, TFX, Vertex AI and…A look back over my KaggleX BIPOC program projectFeb 131Feb 131
InTowards Data SciencebyArtur Lunardi Di FanteCI/CD for TFX Pipelines with Vertex and AI PlatformDeploy a TFX Pipeline with Vertex Pipelines, serve your model on AI Platform, monitor your requests and build a CI/CD pipeline to scale…Oct 18, 20222Oct 18, 20222
InTowards Data SciencebyAkila SomasundaramTensorFlow Transform: Ensuring Seamless Data Preparation in ProductionLeveraging TensorFlow Transform for scaling data pipelines for production environmentsJul 8
Manjinder SinghEnsuring Model Reliability in the Real World: A Guide to TensorFlow Data Validation (TFDV)Building a machine-learning solution in a Jupyter Notebook is one thing, but deploying it in the real world is another. In real-time…Dec 27, 20231
InTowards Data SciencebyAkila SomasundaramValidating Data in a Production Pipeline: The TFX WayA deep dive into data validation using Tensorflow Data ValidationJun 22
InThe Deep HubbyEva RevearMLOps with KaggleX: Deploying a Recommendation System with Tensorflow, TFX, Vertex AI and…A look back over my KaggleX BIPOC program projectFeb 131
InTowards Data SciencebyArtur Lunardi Di FanteCI/CD for TFX Pipelines with Vertex and AI PlatformDeploy a TFX Pipeline with Vertex Pipelines, serve your model on AI Platform, monitor your requests and build a CI/CD pipeline to scale…Oct 18, 20222
InGoogle Developer ExpertsbyPark ChansungMLOps: Big Picture in GCP“Why do we need different CI/CD for machine learning?” the simplest answer is “because the data changes over time whether or not you want”.May 11, 2021
InTowards Data SciencebyArtur Lunardi Di FanteSentiment Analysis with TFX Pipelines — Local DeployBuild a local TFX pipeline, create a sentiment analysis model using the Transformer architecture and serve the model with TF ServingOct 18, 2022
InCARBON CONSULTINGbyMuhammet Nusret ÖzateşWhy you should serve your Tensorflow model using TF Serving?Let’s say you have an AI task to solve. You get the data, clean the data, trained a model with it, and find the best hyperparameters. After…Sep 9, 2021