Fine-Tuning ViT Classifier with Custom Data and Docker Inference - Part 4
Offered By: The Machine Learning Engineer via YouTube
Course Description
Overview
Learn how to fine-tune a Vision Transformer (ViT) model with your own dataset in this comprehensive tutorial. Explore the process of productionizing the model using Docker and FastAPI, gaining valuable insights into machine learning operations (MLOps). Discover practical techniques for customizing and deploying ViT classifiers, enhancing your skills in image classification and model deployment.
Syllabus
LLMOps: Fine Tune ViT Classifier with your own data (Docker inference) #machinelearning
Taught by
The Machine Learning Engineer
Related Courses
Developing a Tabular Data ModelMicrosoft via edX Data Science in Action - Building a Predictive Churn Model
SAP Learning Serverless Machine Learning with Tensorflow on Google Cloud Platform 日本語版
Google Cloud via Coursera Intro to TensorFlow em Português Brasileiro
Google Cloud via Coursera Serverless Machine Learning con TensorFlow en GCP
Google Cloud via Coursera