Hyperparameter Tuning Courses and Certifications

Machine Learning with scikit-learn

14 ratings at DataCamp

Learn how to build and tune predictive models and evaluate how well they'll perform on unseen data.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Supervised Learning with scikit-learn

Grow your machine learning skills with scikit-learn in Python. Use real-world datasets in this interactive course and learn how to make powerful predictions!

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Machine Learning with Tree-Based Models in Python

In this course, you'll learn how to use tree-based models and ensembles for regression and classification using scikit-learn.

• DataCamp
• 5 hours
• Self-Paced
• Free Trial Available

Linear Classifiers in Python

In this course you will learn the details of linear classifiers like logistic regression and SVM.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Extreme Gradient Boosting with XGBoost

Learn the fundamentals of gradient boosting and build state-of-the-art machine learning models using XGBoost to solve classification and regression problems.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Model Validation in Python

Learn the basics of model validation, validation techniques, and begin creating validated and high performing models.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Machine Learning in the Tidyverse

Leverage tidyr and purrr packages in the tidyverse to generate, explore, and evaluate machine learning models.

• DataCamp
• 5 hours
• Self-Paced
• Free Trial Available

Machine Learning with Tree-Based Models in R

Learn how to use tree-based models and ensembles to make classification and regression predictions with tidymodels.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

CI/CD for Machine Learning

Elevate your Machine Learning Development with CI/CD using GitHub Actions and Data Version Control

• DataCamp
• 5 hours
• Self-Paced
• Free Trial Available

Fully Automated MLOps

Learn about MLOps architecture, CI/CD/CM/CT techniques, and automation patterns to deploy ML systems that can deliver value over time.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Predicting CTR with Machine Learning in Python

Learn how to predict click-through rates on ads and implement basic machine learning models in Python so that you can see how to better optimize your ads.

• DataCamp
• 4 hours
• Self-Paced
• Free Trial Available

Supervised Machine Learning in R

Generate, explore, evaluate, and tune the parameters of different supervised machine learning models.

• DataCamp
• 1 day 1 hour
• Self-Paced
• Free Trial Available

Career Certificate

Journey into Machine Learning with Sklearn and Tensorflow

446 ratings at CodeSignal

Dive into machine learning fundamentals through advanced deep learning, mastering data preprocessing, model optimization, and neural networks using real-world datasets with Sklearn and Tensorflow frameworks.

• CodeSignal
• 16 hours
• Self-Paced
• Free Certificate
• 5 courses

Databricks

Efficient Distributed Hyperparameter Tuning with Apache Spark

Learn to efficiently distribute hyperparameter tuning workloads using Apache Spark, avoiding common pitfalls and optimizing performance. Explore best practices with Hyperopt and joblib-spark for scaling ML model training.

• YouTube
• 26 minutes
• Self-Paced
• Free Video

Julia Silge

Hyperparameter Tuning Using Tidymodels

Explore hyperparameter tuning for random forest models using global food consumption data, enhancing model performance and gaining insights into international dietary patterns.

• YouTube
• 30 minutes
• Self-Paced
• Free Video