YoVDO

MLOps: Databricks MLFlow and Optuna Hyper-parameter Tuning

Offered By: The Machine Learning Engineer via YouTube

Tags

MLOps Courses Machine Learning Courses Databricks Courses Hyperparameter Tuning Courses XGBoost Courses MLFlow Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore hyperparameter tuning of an XGBoost model using Databricks, MLflow, and Optuna in this 37-minute video tutorial. Learn how to leverage these powerful tools in combination to optimize machine learning models. Gain hands-on experience with MLOps practices as you follow along with the step-by-step demonstration. Access the accompanying code on GitHub to further enhance your understanding and apply the techniques to your own projects.

Syllabus

MLOps MLFlow: Databricks MLFLow and Optuna Hyper-parameter Tuning


Taught by

The Machine Learning Engineer

Related Courses

Introduction to Artificial Intelligence
Stanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent